diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 0000000000000000000000000000000000000000..6cc1ff3fcb994bd2d321a58af11862aaae88e1db --- /dev/null +++ b/Dockerfile @@ -0,0 +1,32 @@ +FROM python:3.9 + +RUN apt-get update && \ + apt-get install -y --no-install-recommends \ + ffmpeg + +RUN python3 -m pip install --upgrade pip + +# Python installation +WORKDIR /usr/src/app + +# Note: First installing the python requirements permits to save time when re-building after a source change. +COPY requirements.txt /usr/src/app/requirements.txt +RUN cd /usr/src/app/ && pip3 install -r requirements.txt + +# Copy source +COPY setup.py /usr/src/app/setup.py +COPY whisper_timestamped /usr/src/app/whisper_timestamped + +# Install +RUN cd /usr/src/app/ && pip3 install ".[dev]" +RUN cd /usr/src/app/ && pip3 install ".[vad_silero]" +RUN cd /usr/src/app/ && pip3 install ".[vad_auditok]" +RUN cd /usr/src/app/ && pip3 install ".[test]" + +# Cleanup +RUN rm -R /usr/src/app/requirements.txt /usr/src/app/setup.py /usr/src/app/whisper_timestamped + +# Copy tests +COPY tests /usr/src/app/tests + +ENTRYPOINT ["/bin/bash"] \ No newline at end of file diff --git a/Dockerfile.cpu b/Dockerfile.cpu new file mode 100644 index 0000000000000000000000000000000000000000..dceffbfc595003c75680694d24e4de72536559c7 --- /dev/null +++ b/Dockerfile.cpu @@ -0,0 +1,35 @@ +FROM python:3.9 + +RUN apt-get update && \ + apt-get install -y --no-install-recommends \ + ffmpeg + +RUN python3 -m pip install --upgrade pip + +# Python installation +WORKDIR /usr/src/app + +# Force CPU versions of torch +RUN pip3 install \ + torch==1.13.1+cpu \ + torchaudio==0.13.1+cpu \ + -f https://download.pytorch.org/whl/torch_stable.html + +# Note: First installing the python requirements permits to save time when re-building after a source change. +COPY requirements.txt /usr/src/app/requirements.txt +RUN cd /usr/src/app/ && pip3 install -r requirements.txt + +# Copy source +COPY setup.py /usr/src/app/setup.py +COPY whisper_timestamped /usr/src/app/whisper_timestamped + +# Install +RUN cd /usr/src/app/ && pip3 install ".[dev]" + +# Cleanup +RUN rm -R /usr/src/app/requirements.txt /usr/src/app/setup.py /usr/src/app/whisper_timestamped + +# Copy tests +COPY tests /usr/src/app/tests + +ENTRYPOINT ["/bin/bash"] \ No newline at end of file diff --git a/LICENCE b/LICENCE new file mode 100644 index 0000000000000000000000000000000000000000..0ad25db4bd1d86c452db3f9602ccdbe172438f52 --- /dev/null +++ b/LICENCE @@ -0,0 +1,661 @@ + GNU AFFERO GENERAL PUBLIC LICENSE + Version 3, 19 November 2007 + + Copyright (C) 2007 Free Software Foundation, Inc. + Everyone is permitted to copy and distribute verbatim copies + of this license document, but changing it is not allowed. + + Preamble + + The GNU Affero General Public License is a free, copyleft license for +software and other kinds of works, specifically designed to ensure +cooperation with the community in the case of network server software. + + The licenses for most software and other practical works are designed +to take away your freedom to share and change the works. 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It is safest +to attach them to the start of each source file to most effectively +state the exclusion of warranty; and each file should have at least +the "copyright" line and a pointer to where the full notice is found. + + + Copyright (C) + + This program is free software: you can redistribute it and/or modify + it under the terms of the GNU Affero General Public License as published + by the Free Software Foundation, either version 3 of the License, or + (at your option) any later version. + + This program is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU Affero General Public License for more details. + + You should have received a copy of the GNU Affero General Public License + along with this program. If not, see . + +Also add information on how to contact you by electronic and paper mail. + + If your software can interact with users remotely through a computer +network, you should also make sure that it provides a way for users to +get its source. For example, if your program is a web application, its +interface could display a "Source" link that leads users to an archive +of the code. There are many ways you could offer source, and different +solutions will be better for different programs; see section 13 for the +specific requirements. + + You should also get your employer (if you work as a programmer) or school, +if any, to sign a "copyright disclaimer" for the program, if necessary. +For more information on this, and how to apply and follow the GNU AGPL, see +. diff --git a/README.md b/README.md index b395ff064c4df0831530d702e0288acad5833a67..3dd9f012eba8e700398aa4bd4a12d6e8a01d198e 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,416 @@ ---- -license: agpl-3.0 ---- +# whisper-timestamped + +Multilingual Automatic Speech Recognition with word-level timestamps and confidence. + +* [Description](#description) + * [Notes on other approaches](#notes-on-other-approaches) +* [Installation](#installation) + * [First installation](#first-installation) + * [Additional packages that might be needed](#additional-packages-that-might-be-needed) + * [Docker](#docker) + * [Light installation for CPU](#light-installation-for-cpu) + * [Upgrade to the latest version](#upgrade-to-the-latest-version) +* [Usage](#usage) + * [Python](#python) + * [Command line](#command-line) + * [Plot of word alignment](#plot-of-word-alignment) + * [Example output](#example-output) + * [Options that may improve results](#options-that-may-improve-results) + * [Accurate Whisper transcription](#accurate-whisper-transcription) + * [Running Voice Activity Detection (VAD) before sending to Whisper](#running-voice-activity-detection-vad-before-sending-to-whisper) + * [Detecting disfluencies](#detecting-disfluencies) +* [Acknowlegment](#acknowlegment) +* [Citations](#citations) + +## Description + +[Whisper](https://openai.com/blog/whisper/) is a set of multi-lingual, robust speech recognition models trained by OpenAI that achieve state-of-the-art results in many languages. Whisper models were trained to predict approximate timestamps on speech segments (most of the time with 1-second accuracy), but they cannot originally predict word timestamps. This repository proposes an implementation to **predict word timestamps and provide a more accurate estimation of speech segments when transcribing with Whisper models**. +Besides, a confidence score is assigned to each word and each segment. + +The approach is based on Dynamic Time Warping (DTW) applied to cross-attention weights, as demonstrated by [this notebook by Jong Wook Kim](https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/notebooks/Multilingual_ASR.ipynb). There are some additions to this notebook: +* The start/end estimation is more accurate. +* Confidence scores are assigned to each word. +* **If possible (without beam search...)**, no additional inference steps are required to predict word timestamps (word alignment is done on the fly after each speech segment is decoded). +* Special care has been taken regarding memory usage: `whisper-timestamped` is able to process long files with little additional memory compared to the regular use of the Whisper model. + +`whisper-timestamped` is an extension of the [`openai-whisper`](https://pypi.org/project/whisper-openai/) Python package and is meant to be compatible with any version of `openai-whisper`. +It provides more efficient/accurate word timestamps, along with those additional features: +* Voice Activity Detection (VAD) can be run before applying Whisper model, + to avoid hallucinations due to errors in the training data (for instance, predicting "Thanks you for watching!" on pure silence). + Several VAD methods are available: silero (default), auditok, auditok:v3.1 +* When the language is not specified, the language probabilities are provided among the outputs. + +### Notes on other approaches + +An alternative relevant approach to recovering word-level timestamps involves using wav2vec models that predict characters, as successfully implemented in [whisperX](https://github.com/m-bain/whisperX). However, these approaches have several drawbacks that are not present in approaches based on cross-attention weights such as `whisper_timestamped`. These drawbacks include: +* The need to find one wav2vec model per language to support, which does not scale well with the multi-lingual capabilities of Whisper. +* The need to handle (at least) one additional neural network (wav2vec model), which consumes memory. +* The need to normalize characters in Whisper transcription to match the character set of the wav2vec model. This involves awkward language-dependent conversions, such as converting numbers to words ("2" -> "two"), symbols to words ("%" -> "percent", "€" -> "euro(s)")... +* The lack of robustness around speech disfluencies (fillers, hesitations, repeated words...) that are usually removed by Whisper. + +An alternative approach that does not require an additional model is to look at the probabilities of timestamp tokens estimated by the Whisper model after each (sub)word token is predicted. This was implemented, for instance, in whisper.cpp and stable-ts. However, this approach lacks robustness because Whisper models have not been trained to output meaningful timestamps after each word. Whisper models tend to predict timestamps only after a certain number of words have been predicted (typically at the end of a sentence), and the probability distribution of timestamps outside this condition may be inaccurate. In practice, these methods can produce results that are totally out-of-sync on some periods of time (we observed this especially when there is jingle music). Also, the timestamp precision of Whisper models tends to be rounded to 1 second (as in many video subtitles), which is too inaccurate for words, and reaching better accuracy is tricky. + +## Installation + +### First installation + +Requirements: +* `python3` (version higher or equal to 3.7, at least 3.9 is recommended) +* `ffmpeg` (see instructions for installation on the [whisper repository](https://github.com/openai/whisper)) + +You can install `whisper-timestamped` either by using pip: +```bash +pip3 install whisper-timestamped +``` + +or by cloning this repository and running installation: +```bash +git clone https://github.com/linto-ai/whisper-timestamped +cd whisper-timestamped/ +python3 setup.py install +``` + +#### Additional packages that might be needed + +If you want to plot alignment between audio timestamps and words (as in [this section](#plot-of-word-alignment)), you also need matplotlib: +```bash +pip3 install matplotlib +``` + +If you want to use VAD option (Voice Activity Detection before running Whisper model), you also need torchaudio and onnxruntime: +```bash +pip3 install onnxruntime torchaudio +``` + +If you want to use finetuned Whisper models from the Hugging Face Hub, you also need transformers: +```bash +pip3 install transformers +``` + +#### Docker + +A docker image of about 9GB can be built using: +```bash +git clone https://github.com/linto-ai/whisper-timestamped +cd whisper-timestamped/ +docker build -t whisper_timestamped:latest . +``` + +### Light installation for CPU + +If you don't have a GPU (or don't want to use it), then you don't need to install the CUDA dependencies. You should then just install a light version of torch **before** installing whisper-timestamped, for instance as follows: +```bash +pip3 install \ + torch==1.13.1+cpu \ + torchaudio==0.13.1+cpu \ + -f https://download.pytorch.org/whl/torch_stable.html +``` + +A specific docker image of about 3.5GB can also be built using: +```bash +git clone https://github.com/linto-ai/whisper-timestamped +cd whisper-timestamped/ +docker build -t whisper_timestamped_cpu:latest -f Dockerfile.cpu . +``` + +### Upgrade to the latest version + +When using pip, the library can be updated to the latest version using: +``` +pip3 install --upgrade --no-deps --force-reinstall git+https://github.com/linto-ai/whisper-timestamped +``` + +A specific version of `openai-whisper` can be used by running, for example: +```bash +pip3 install openai-whisper==20230124 +``` + +## Usage + +### Python + +In Python, you can use the function `whisper_timestamped.transcribe()`, which is similar to the function `whisper.transcribe()`: +```python +import whisper_timestamped +help(whisper_timestamped.transcribe) +``` +The main difference with `whisper.transcribe()` is that the output will include a key `"words"` for all segments, with the word start and end position. Note that the word will include punctuation. See the example [below](#example-output). + +Besides, the default decoding options are different to favour efficient decoding (greedy decoding instead of beam search, and no temperature sampling fallback). To have same default as in `whisper`, use ```beam_size=5, best_of=5, temperature=(0.0, 0.2, 0.4, 0.6, 0.8, 1.0)```. + +There are also additional options related to word alignement. + +In general, if you import `whisper_timestamped` instead of `whisper` in your Python script and use `transcribe(model, ...)` instead of `model.transcribe(...)`, it should do the job: +``` +import whisper_timestamped as whisper + +audio = whisper.load_audio("AUDIO.wav") + +model = whisper.load_model("tiny", device="cpu") + +result = whisper.transcribe(model, audio, language="fr") + +import json +print(json.dumps(result, indent = 2, ensure_ascii = False)) +``` + +Note that you can use a finetuned Whisper model from HuggingFace or a local folder by using the `load_model` method of `whisper_timestamped`. For instance, if you want to use [whisper-large-v2-nob](https://huggingface.co/NbAiLab/whisper-large-v2-nob), you can simply do the following: +``` +import whisper_timestamped as whisper + +model = whisper.load_model("NbAiLab/whisper-large-v2-nob", device="cpu") + +# ... +``` + +### Command line + +You can also use `whisper_timestamped` on the command line, similarly to `whisper`. See help with: +```bash +whisper_timestamped --help +``` + +The main differences with `whisper` CLI are: +* Output files: + * The output JSON contains word timestamps and confidence scores. See example [below](#example-output). + * There is an additional CSV output format. + * For SRT, VTT, TSV formats, there will be additional files saved with word timestamps. +* Some default options are different: + * By default, no output folder is set: Use `--output_dir .` for Whisper default. + * By default, there is no verbose: Use `--verbose True` for Whisper default. + * By default, beam search decoding and temperature sampling fallback are disabled, to favour an efficient decoding. + To set the same as Whisper default, you can use `--accurate` (which is an alias for ```--beam_size 5 --temperature_increment_on_fallback 0.2 --best_of 5```). +* There are some additional specific options: + + * `--compute_confidence` to enable/disable the computation of confidence scores for each word. + * `--punctuations_with_words` to decide whether punctuation marks should be included or not with preceding words. + +An example command to process several files using the `tiny` model and output the results in the current folder, as would be done by default with whisper, is as follows: +``` +whisper_timestamped audio1.flac audio2.mp3 audio3.wav --model tiny --output_dir . +``` + +Note that you can use a fine-tuned Whisper model from HuggingFace or a local folder. For instance, if you want to use the [whisper-large-v2-nob](https://huggingface.co/NbAiLab/whisper-large-v2-nob) model, you can simply do the following: +``` +whisper_timestamped --model NbAiLab/whisper-large-v2-nob <...> +``` + +### Plot of word alignment + +Note that you can use the `plot_word_alignment` option of the `whisper_timestamped.transcribe()` Python function or the `--plot` option of the `whisper_timestamped` CLI to see the word alignment for each segment. + +![Example alignement](figs/example_alignement_plot.png) + +* The upper plot represents the transformation of cross-attention weights used for alignment with Dynamic Time Warping. The abscissa represents time, and the ordinate represents the predicted tokens, with special timestamp tokens at the beginning and end, and (sub)words and punctuation in the middle. +* The lower plot is an MFCC representation of the input signal (features used by Whisper, based on Mel-frequency cepstrum). +* The vertical dotted red lines show where the word boundaries are found (with punctuation marks "glued" to the previous word). + +### Example output + +The output of `whisper_timestamped.transcribe()` function is a python dictionary, +which can be viewed in JSON format using the CLI. + +The JSON schema can be seen in [tests/json_schema.json](tests/json_schema.json). + +Here is an example output: +```bash +whisper_timestamped AUDIO_FILE.wav --model tiny --language fr +``` +```json +{ + "text": " Bonjour! Est-ce que vous allez bien?", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.5, + "end": 1.2, + "text": " Bonjour!", + "tokens": [ 25431, 2298 ], + "temperature": 0.0, + "avg_logprob": -0.6674491882324218, + "compression_ratio": 0.8181818181818182, + "no_speech_prob": 0.10241222381591797, + "confidence": 0.51, + "words": [ + { + "text": "Bonjour!", + "start": 0.5, + "end": 1.2, + "confidence": 0.51 + } + ] + }, + { + "id": 1, + "seek": 200, + "start": 2.02, + "end": 4.48, + "text": " Est-ce que vous allez bien?", + "tokens": [ 50364, 4410, 12, 384, 631, 2630, 18146, 3610, 2506, 50464 ], + "temperature": 0.0, + "avg_logprob": -0.43492694334550336, + "compression_ratio": 0.7714285714285715, + "no_speech_prob": 0.06502953916788101, + "confidence": 0.595, + "words": [ + { + "text": "Est-ce", + "start": 2.02, + "end": 3.78, + "confidence": 0.441 + }, + { + "text": "que", + "start": 3.78, + "end": 3.84, + "confidence": 0.948 + }, + { + "text": "vous", + "start": 3.84, + "end": 4.0, + "confidence": 0.935 + }, + { + "text": "allez", + "start": 4.0, + "end": 4.14, + "confidence": 0.347 + }, + { + "text": "bien?", + "start": 4.14, + "end": 4.48, + "confidence": 0.998 + } + ] + } + ], + "language": "fr" +} +``` +If the language is not specified (e.g. without option `--language fr` in the CLI) you will find an additional key with the language probabilities: +```json +{ + ... + "language": "fr", + "language_probs": { + "en": 0.027954353019595146, + "zh": 0.02743500843644142, + ... + "fr": 0.9196318984031677, + ... + "su": 3.0119704064190955e-08, + "yue": 2.2565967810805887e-05 + } +} +``` + +### Options that may improve results + +Here are some options that are not enabled by default but might improve results. + +#### Accurate Whisper transcription + +As mentioned earlier, some decoding options are disabled by default to offer better efficiency. However, this can impact the quality of the transcription. To run with the options that have the best chance of providing a good transcription, use the following options. +* In Python: +```python +results = whisper_timestamped.transcribe(model, audio, beam_size=5, best_of=5, temperature=(0.0, 0.2, 0.4, 0.6, 0.8, 1.0), ...) +``` +* On the command line: +```bash +whisper_timestamped --accurate ... +``` + +#### Running Voice Activity Detection (VAD) before sending to Whisper + +Whisper models can "hallucinate" text when given a segment without speech. This can be avoided by running VAD and gluing speech segments together before transcribing with the Whisper model. This is possible with `whisper-timestamped`. +* In Python: +```python +results = whisper_timestamped.transcribe(model, audio, vad=True, ...) +``` +* On the command line: +```bash +whisper_timestamped --vad True ... +``` + +By default, the VAD method used is [silero](https://github.com/snakers4/silero-vad). +But other methods are available, such as earlier versions of silero, or [auditok](https://github.com/amsehili/auditok). +Those methods were introduced because latest versions of silero VAD can have a lot of false alarms on some audios (speech detected on silence). +* In Python: +```python +results = whisper_timestamped.transcribe(model, audio, vad="silero:v3.1", ...) +results = whisper_timestamped.transcribe(model, audio, vad="auditok", ...) +``` +* On the command line: +```bash +whisper_timestamped --vad silero:v3.1 ... +whisper_timestamped --vad auditok ... +``` + +In order to watch the VAD results, you can use the `--plot` option of the `whisper_timestamped` CLI, +or the `plot_word_alignment` option of the `whisper_timestamped.transcribe()` Python function. +It will show the VAD results on the input audio signal as following (x-axis is time in seconds): +| **vad="silero:v4.0"** | **vad="silero:v3.1"** | **vad="auditok"** | +| :---: | :---: | :---: | +| ![Example VAD](figs/VAD_silero_v4.0.png) | ![Example VAD](figs/VAD_silero_v3.1.png) | ![Example VAD](figs/VAD_auditok.png) | + +#### Detecting disfluencies + +Whisper models tend to remove speech disfluencies (filler words, hesitations, repetitions, etc.). Without precautions, the disfluencies that are not transcribed will affect the timestamp of the following word: the timestamp of the beginning of the word will actually be the timestamp of the beginning of the disfluencies. `whisper-timestamped` can have some heuristics to avoid this. +* In Python: +```python +results = whisper_timestamped.transcribe(model, audio, detect_disfluencies=True, ...) +``` +* On the command line: +```bash +whisper_timestamped --detect_disfluencies True ... +``` +**Important:** Note that when using these options, possible disfluencies will appear in the transcription as a special "`[*]`" word. + + +## Acknowlegment +* [whisper](https://github.com/openai/whisper): Whisper speech recognition (License MIT). +* [dtw-python](https://pypi.org/project/dtw-python): Dynamic Time Warping (License GPL v3). + +## Citations +If you use this in your research, please cite the repo: + +```bibtex +@misc{lintoai2023whispertimestamped, + title={whisper-timestamped}, + author={Louradour, J{\'e}r{\^o}me}, + journal={GitHub repository}, + year={2023}, + publisher={GitHub}, + howpublished = {\url{https://github.com/linto-ai/whisper-timestamped}} +} +``` + +as well as the OpenAI Whisper paper: + +```bibtex +@article{radford2022robust, + title={Robust speech recognition via large-scale weak supervision}, + author={Radford, Alec and Kim, Jong Wook and Xu, Tao and Brockman, Greg and McLeavey, Christine and Sutskever, Ilya}, + journal={arXiv preprint arXiv:2212.04356}, + year={2022} +} +``` + +and this paper for Dynamic-Time-Warping: + +```bibtex +@article{JSSv031i07, + title={Computing and Visualizing Dynamic Time Warping Alignments in R: The dtw Package}, + author={Giorgino, Toni}, + journal={Journal of Statistical Software}, + year={2009}, + volume={31}, + number={7}, + doi={10.18637/jss.v031.i07} +} +``` diff --git a/figs/VAD_auditok.png b/figs/VAD_auditok.png new file mode 100644 index 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0000000000000000000000000000000000000000..f5a15670950a2dca208b867d00ff408e2cd577f3 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,3 @@ +Cython +dtw-python +openai-whisper \ No newline at end of file diff --git a/setup.py b/setup.py new file mode 100644 index 0000000000000000000000000000000000000000..d3e55caa5f5f0e202f9ce77afea457b8bbd60a46 --- /dev/null +++ b/setup.py @@ -0,0 +1,58 @@ +import os + +from setuptools import setup, find_packages + +install_requires = [ + "Cython", + "dtw-python", + "openai-whisper", +] + +required_packages_filename = os.path.join(os.path.dirname(__file__), "requirements.txt") +if os.path.exists(required_packages_filename): + install_requires2 = [l.strip() for l in open(required_packages_filename).readlines()] + assert install_requires == install_requires2, f"requirements.txt is not up-to-date: {install_requires} != {install_requires2}" + +version = None +license = None +with open(os.path.join(os.path.dirname(__file__), "whisper_timestamped", "transcribe.py")) as f: + for line in f: + if line.strip().startswith("__version__"): + version = line.split("=")[1].strip().strip("\"'") + if version and license: + break + if line.strip().startswith("__license__"): + license = line.split("=")[1].strip().strip("\"'") + if version and license: + break +assert version and license + +description="Multi-lingual Automatic Speech Recognition (ASR) based on Whisper models, with accurate word timestamps, access to language detection confidence, several options for Voice Activity Detection (VAD), and more." + +setup( + name="whisper-timestamped", + py_modules=["whisper_timestamped"], + version=version, + description=description, + long_description=description+"\nSee https://github.com/linto-ai/whisper-timestamped for more information.", + long_description_content_type='text/markdown', + python_requires=">=3.7", + author="Jeronymous", + url="https://github.com/linto-ai/whisper-timestamped", + license=license, + packages=find_packages(exclude=["tests*"]), + install_requires=install_requires, + entry_points = { + 'console_scripts': [ + 'whisper_timestamped=whisper_timestamped.transcribe:cli', + 'whisper_timestamped_make_subtitles=whisper_timestamped.make_subtitles:cli' + ], + }, + include_package_data=True, + extras_require={ + 'dev': ['matplotlib==3.7.4', 'transformers'], + 'vad_silero': ['onnxruntime', 'torchaudio'], + 'vad_auditok': ['auditok'], + 'test': ['jsonschema'], + }, +) diff --git a/tests/__init__.py b/tests/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..8b137891791fe96927ad78e64b0aad7bded08bdc --- /dev/null +++ b/tests/__init__.py @@ -0,0 +1 @@ + diff --git a/tests/data/apollo11.mp3 b/tests/data/apollo11.mp3 new file mode 100644 index 0000000000000000000000000000000000000000..d9246ca9f73701df5270dd342bdca2d316eda5b3 Binary files /dev/null and b/tests/data/apollo11.mp3 differ diff --git a/tests/data/bonjour.wav b/tests/data/bonjour.wav new file mode 100644 index 0000000000000000000000000000000000000000..f03944e35c448f2226923356f7208d0234a6419a Binary files /dev/null and b/tests/data/bonjour.wav differ diff --git a/tests/data/bonjour_vous_allez_bien.mp3 b/tests/data/bonjour_vous_allez_bien.mp3 new file mode 100644 index 0000000000000000000000000000000000000000..53bd078e6610cca0bddf7dbcaff2b2a991028c51 Binary files /dev/null and b/tests/data/bonjour_vous_allez_bien.mp3 differ diff --git a/tests/data/empty.mp3 b/tests/data/empty.mp3 new file mode 100644 index 0000000000000000000000000000000000000000..a73b2f2f14d2f33beb872041f64abc0208eee70b Binary files /dev/null and b/tests/data/empty.mp3 differ diff --git a/tests/data/empty.wav b/tests/data/empty.wav new file mode 100644 index 0000000000000000000000000000000000000000..a15eb0580e1a5cd7cd4b4d3e610155a3a967c81b Binary files /dev/null and b/tests/data/empty.wav differ diff --git a/tests/data/gaenswein15.mp3 b/tests/data/gaenswein15.mp3 new file mode 100644 index 0000000000000000000000000000000000000000..48689cfe8af4a3873f7c988793bd48ab12523094 Binary files /dev/null and b/tests/data/gaenswein15.mp3 differ diff --git a/tests/data/gloria.mp3 b/tests/data/gloria.mp3 new file mode 100644 index 0000000000000000000000000000000000000000..8289f3989deb8bccd19b102b9530974600791798 Binary files /dev/null and b/tests/data/gloria.mp3 differ diff --git a/tests/data/japanese.mp3 b/tests/data/japanese.mp3 new file mode 100644 index 0000000000000000000000000000000000000000..10337faea507f73c0add491837ad997e5656741a Binary files /dev/null and b/tests/data/japanese.mp3 differ diff --git a/tests/data/laugh1.mp3 b/tests/data/laugh1.mp3 new file mode 100644 index 0000000000000000000000000000000000000000..c564abe8c4f87cbaa1ee1998f17a36a1592f5c61 Binary files /dev/null and b/tests/data/laugh1.mp3 differ diff --git a/tests/data/laugh2.mp3 b/tests/data/laugh2.mp3 new file mode 100644 index 0000000000000000000000000000000000000000..b8fb8840f31d416eab241969a1b5f2da067a6acf Binary files /dev/null and b/tests/data/laugh2.mp3 differ diff --git a/tests/data/no_punctuations.mp3.words.json b/tests/data/no_punctuations.mp3.words.json new file mode 100644 index 0000000000000000000000000000000000000000..46d20abcf33869ed2f4eda32988e19619cfaf7b4 --- /dev/null +++ b/tests/data/no_punctuations.mp3.words.json @@ -0,0 +1,68 @@ +{ + "text": " Dis-moi, est-ce que l'avion vole?", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.4, + "end": 2.34, + "text": " Dis-moi, est-ce que l'avion vole?", + "tokens": [ + 50364, + 4208, + 12, + 29292, + 11, + 871, + 12, + 384, + 631, + 287, + 6, + 706, + 313, + 49877, + 2506, + 50494 + ], + "temperature": 0.0, + "avg_logprob": -0.3014036907869227, + "compression_ratio": 0.8048780487804879, + "no_speech_prob": 0.05134102329611778, + "confidence": 0.925, + "words": [ + { + "text": "Dis-moi", + "start": 0.4, + "end": 1.36, + "confidence": 0.801 + }, 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0000000000000000000000000000000000000000..9c1c12473bf6c5485426a4f563b1385fd039f243 Binary files /dev/null and b/tests/data/smartphone.mp3 differ diff --git a/tests/data/smartphone.mp3.words.json b/tests/data/smartphone.mp3.words.json new file mode 100644 index 0000000000000000000000000000000000000000..8cf211f5b9abc1b522e115e190503add6af20a12 --- /dev/null +++ b/tests/data/smartphone.mp3.words.json @@ -0,0 +1,4802 @@ +{ + "text": " C'est évident ce que dit Nicolas, mais je ne me l'étais jamais formulé comme ça. Ce qui fait la force du smartphone, c'est pas seulement l'accumulation des fonctions, mais la manière dont elles interagissent entre elles. Ce qui dit d'ailleurs sur la photo, c'est hyper convaincant. Alors évidemment, il faudrait ajouter les interfaces. L'écran tactile a été beaucoup très souvent mentionné. Mais bon, il faut dire qu'il profite aussi de 20 ans pendant lesquels les ordinateurs nous ont appris à cliquer sur des icônes. Sauf que le smartphone ajoute le toucher, ce qui rend le contact plus direct, plus sensible. Et puis évidemment, il faudrait parler aussi des applications qui permettent de contourner le côté touffu de la navigation web pour aller directement au but. Bref, tout ça, ce sont les conditions qui permettent de créer cet objet dont Nicolas dit qu'il est vraisemblablement inédit dans l'histoire de l'humanité. Mais ça, ça soulève une autre interrogation. Est-ce que le fait que cet objet soit inédit induit que notre rapport à lui est aussi un rapport inédit? Je veux dire, est-ce que le rapport qu'on a au smartphone est comparable à celui qu'on entretenait à d'autres objets techniques comme la voiture ou le téléphone? Il n'y a pas d'équivalent en fait. Et donc cette espèce de nouveauté dans la relation à l'objet, c'est fascinant et terrifiant. Parce qu'on a l'impression, comme le disent les utilisateurs et les services, d'être dépendants de cet objet, d'induire en fait une espèce de relation, de médiation avec le monde qui rend de l'ampleur et qui amène aussi à des formes de rejet. Donc, à objet inédit, rapport inédit. Et ce rapport, si j'en crois Nicolas, serait caractérisé par un mélange de dépendance et de rejet. Bon, en vrai, il faudrait remonter très très finement toute l'histoire des objets techniques et de leur insertion dans nos vies pour déterminer si ce rapport est totalement inédit. Mais j'ai l'impression comme ça que Nicolas ne se trompe pas vraiment. Pour autant que je sache, il y a eu plein de discussions autour de la voiture ou même du téléphone. Mais la dépendance n'était pas du même ordre. Donc le rejet non plus n'était pas du même ordre. On peut adorer sa bagnole, en avoir besoin pour plein de choses. Et bien, le soir, quand on va se coucher, on la laisse. On ne l'a pas dans la main quand on est au lit, on ne l'emmène pas au chiottes. On pouvait être énervé par son môme qui occupait la ligne de téléphone pendant une heure chaque soir pour discuter avec un copain. Mais ça ne ressemblait pas à ce qu'on peut ressentir à voir ce même môme aujourd'hui, continuellement avec son smartphone dans la main, comme si c'était une sorte de pacemaker externe, comme si le lâcher allait entraîner sa mort immédiate. Bon, je dis ça pour le môme, mais c'est évidemment valable pour nous aussi. Donc, rapport inédit. D'accord. Mais pourquoi a-t-on l'impression qu'on n'en sortira jamais? Est-ce qu'il faut en remettre la faute sur les gens qui ont créé cet outil merveilleux et diabolique, et diabolique parce que merveilleux? Les économistes parlent de dépendance du sentier. C'est l'idée qu'on est sur un sentier qui a été établi, soit volontairement en marchant dessus, soit en définissant des bornes, en définissant une signalétique.", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.38, + "end": 3.62, + "text": " C'est évident ce que dit Nicolas, mais je ne me l'étais jamais formulé comme ça.", + "tokens": [ + 383, + 6, + 377, + 20090, + 1078, + 1769, + 631, + 6176, + 38268, + 11, + 2420, + 1506, + 408, + 385, + 287, + 6, + 22824, + 14540, + 49990, + 526, + 5173, + 2788, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.2362671656324374, + "compression_ratio": 1.6238532110091743, + "no_speech_prob": 0.15368737280368805, + "confidence": 0.935, + "words": [ + { + "text": "C'est", + "start": 0.38, + "end": 0.58, + "confidence": 0.961 + }, + { + "text": "évident", + "start": 0.58, + "end": 0.88, + "confidence": 0.984 + }, + { + "text": "ce", + "start": 0.88, + "end": 1.02, + "confidence": 0.663 + }, + { + "text": "que", + "start": 1.02, + "end": 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"text": " Ce qui fait la force du smartphone, c'est pas seulement l'accumulation des fonctions,", + "tokens": [ + 8257, + 1956, + 3887, + 635, + 3464, + 1581, + 13307, + 11, + 269, + 6, + 377, + 1736, + 27772, + 287, + 6, + 8476, + 449, + 2776, + 730, + 17290, + 3916, + 11 + ], + "temperature": 0.0, + "avg_logprob": -0.2362671656324374, + "compression_ratio": 1.6238532110091743, + "no_speech_prob": 0.15368737280368805, + "confidence": 0.93, + "words": [ + { + "text": "Ce", + "start": 4.08, + "end": 4.26, + "confidence": 0.952 + }, + { + "text": "qui", + "start": 4.26, + "end": 4.34, + "confidence": 0.958 + }, + { + "text": "fait", + "start": 4.34, + "end": 4.48, + "confidence": 0.567 + }, + { + "text": "la", + "start": 4.48, + "end": 4.66, + "confidence": 0.972 + }, + { + "text": "force", + "start": 4.66, + "end": 5.0, + "confidence": 0.999 + }, + { + "text": "du", + "start": 5.0, + "end": 5.2, + "confidence": 0.996 + }, + { + "text": "smartphone,", + "start": 5.2, + "end": 5.88, + 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16.02, + "text": " Alors évidemment, il faudrait ajouter les interfaces.", + "tokens": [ + 9946, + 24724, + 11, + 1930, + 38694, + 8645, + 17680, + 23985, + 1512, + 28416, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.2362671656324374, + "compression_ratio": 1.6238532110091743, + "no_speech_prob": 0.15368737280368805, + "confidence": 0.912, + "words": [ + { + "text": "Alors", + "start": 13.34, + "end": 13.62, + "confidence": 0.584 + }, + { + "text": "évidemment,", + "start": 13.62, + "end": 14.34, + "confidence": 0.832 + }, + { + "text": "il", + "start": 14.34, + "end": 14.38, + "confidence": 0.953 + }, + { + "text": "faudrait", + "start": 14.38, + "end": 14.74, + "confidence": 0.996 + }, + { + "text": "ajouter", + "start": 14.74, + "end": 15.16, + "confidence": 0.992 + }, + { + "text": "les", + "start": 15.16, + "end": 15.52, + "confidence": 0.985 + }, + { + "text": "interfaces.", + "start": 15.52, + "end": 16.02, + "confidence": 0.984 + } + ] + }, + { + "id": 5, + "seek": 0, + 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45.98, + "end": 46.18, + "confidence": 0.999 + }, + { + "text": "l'humanité.", + "start": 46.18, + "end": 46.58, + "confidence": 0.992 + } + ] + }, + { + "id": 10, + "seek": 2534, + "start": 46.6, + "end": 48.82, + "text": " Mais ça, ça soulève une autre interrogation.", + "tokens": [ + 6313, + 2788, + 11, + 2788, + 5133, + 31397, + 2251, + 15081, + 24871, + 399, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.07923513396173461, + "compression_ratio": 1.6254416961130742, + "no_speech_prob": 3.4465685985196615e-06, + "confidence": 0.969, + "words": [ + { + "text": "Mais", + "start": 46.6, + "end": 47.24, + "confidence": 0.845 + }, + { + "text": "ça,", + "start": 47.24, + "end": 47.72, + "confidence": 0.934 + }, + { + "text": "ça", + "start": 47.72, + "end": 47.76, + "confidence": 0.977 + }, + { + "text": "soulève", + "start": 47.76, + "end": 47.84, + "confidence": 0.993 + }, + { + "text": "une", + "start": 47.84, + "end": 48.02, + "confidence": 0.998 + }, + { + "text": "autre", + "start": 48.02, + "end": 48.26, + "confidence": 0.999 + }, + { + "text": "interrogation.", + "start": 48.26, + "end": 48.82, + "confidence": 0.997 + } + ] + }, + { + "id": 11, + "seek": 4884, + "start": 49.22, + "end": 55.46, + "text": " Est-ce que le fait que cet objet soit inédit induit que notre rapport à lui est aussi un rapport inédit?", + "tokens": [ + 4410, + 12, + 384, + 631, + 476, + 3887, + 631, + 8603, + 14964, + 12703, + 294, + 7811, + 270, + 13716, + 270, + 631, + 10349, + 18018, + 1531, + 8783, + 871, + 6212, + 517, + 18018, + 294, + 7811, + 270, + 2506 + ], + "temperature": 0.0, + "avg_logprob": -0.10683460109281225, + "compression_ratio": 1.662379421221865, + "no_speech_prob": 1.2805365258827806e-05, + "confidence": 0.988, + "words": [ + { + "text": "Est-ce", + "start": 49.22, + "end": 49.62, + "confidence": 0.982 + }, + { + "text": "que", + "start": 49.62, + "end": 49.72, + "confidence": 0.991 + }, + { + "text": "le", + "start": 49.72, + "end": 49.82, + "confidence": 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"c'est", + "start": 70.24, + "end": 70.38, + "confidence": 0.98 + }, + { + "text": "fascinant", + "start": 70.38, + "end": 70.64, + "confidence": 0.978 + }, + { + "text": "et", + "start": 70.64, + "end": 70.76, + "confidence": 0.965 + }, + { + "text": "terrifiant.", + "start": 70.76, + "end": 71.52, + "confidence": 0.977 + } + ] + }, + { + "id": 15, + "seek": 4884, + "start": 71.62, + "end": 76.48, + "text": " Parce qu'on a l'impression, comme le disent les utilisateurs et les services, d'être dépendants de cet objet,", + "tokens": [ + 20429, + 421, + 6, + 266, + 257, + 287, + 6, + 36107, + 11, + 5173, + 476, + 37313, + 1512, + 33643, + 25929, + 1030, + 1512, + 3328, + 11, + 274, + 6, + 9498, + 45768, + 1719, + 368, + 8603, + 14964, + 11 + ], + "temperature": 0.0, + "avg_logprob": -0.10683460109281225, + "compression_ratio": 1.662379421221865, + "no_speech_prob": 1.2805365258827806e-05, + "confidence": 0.815, + "words": [ + { + "text": "Parce", + "start": 71.62, + "end": 71.86, + 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Donc le rejet non plus n'était pas du même ordre.", + "tokens": [ + 6313, + 635, + 45768, + 719, + 297, + 6, + 9743, + 1736, + 1581, + 5698, + 4792, + 265, + 13, + 7477, + 476, + 319, + 7108, + 2107, + 1804, + 297, + 6, + 9743, + 1736, + 1581, + 5698, + 4792, + 265, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.07393737035254909, + "compression_ratio": 1.685512367491166, + "no_speech_prob": 5.3074043535161763e-05, + "confidence": 0.972, + "words": [ + { + "text": "Mais", + "start": 115.34, + "end": 115.72, + "confidence": 0.994 + }, + { + "text": "la", + "start": 115.72, + "end": 116.02, + "confidence": 0.936 + }, + { + "text": "dépendance", + "start": 116.02, + "end": 116.4, + "confidence": 0.997 + }, + { + "text": "n'était", + "start": 116.4, + "end": 116.62, + "confidence": 0.994 + }, + { + "text": "pas", + "start": 116.62, + "end": 117.0, + "confidence": 0.998 + }, + { + "text": "du", + "start": 117.0, + "end": 117.16, + "confidence": 0.995 + }, + { + "text": "même", + 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+ "id": 26, + "seek": 10584, + "start": 126.98, + "end": 130.48, + "text": " On ne l'a pas dans la main quand on est au lit, on ne l'emmène pas au chiottes.", + "tokens": [ + 1282, + 408, + 287, + 6, + 64, + 1736, + 2680, + 635, + 2135, + 6932, + 322, + 871, + 1609, + 7997, + 11, + 322, + 408, + 287, + 6, + 443, + 76, + 18832, + 1736, + 1609, + 13228, + 1521, + 279, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.07393737035254909, + "compression_ratio": 1.685512367491166, + "no_speech_prob": 5.3074043535161763e-05, + "confidence": 0.914, + "words": [ + { + "text": "On", + "start": 126.98, + "end": 127.32, + "confidence": 0.954 + }, + { + "text": "ne", + "start": 127.32, + "end": 127.36, + "confidence": 0.802 + }, + { + "text": "l'a", + "start": 127.36, + "end": 127.48, + "confidence": 0.974 + }, + { + "text": "pas", + "start": 127.48, + "end": 127.68, + "confidence": 0.999 + }, + { + "text": "dans", + "start": 127.68, + "end": 127.8, + "confidence": 0.996 + }, + { + "text": "la", 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D'accord. Mais pourquoi a-t-on l'impression qu'on n'en sortira jamais?", + "tokens": [ + 7477, + 11, + 18018, + 294, + 7811, + 270, + 13, + 413, + 6, + 19947, + 13, + 6313, + 19934, + 257, + 12, + 83, + 12, + 266, + 287, + 6, + 36107, + 421, + 6, + 266, + 297, + 6, + 268, + 1333, + 4271, + 14540, + 2506 + ], + "temperature": 0.0, + "avg_logprob": -0.06175626696962299, + "compression_ratio": 1.6127167630057804, + "no_speech_prob": 1.5689402061980218e-05, + "confidence": 0.948, + "words": [ + { + "text": "Donc,", + "start": 152.34, + "end": 153.46, + "confidence": 0.991 + }, + { + "text": "rapport", + "start": 153.46, + "end": 153.66, + "confidence": 0.977 + }, + { + "text": "inédit.", + "start": 153.66, + "end": 154.24, + "confidence": 0.997 + }, + { + "text": "D'accord.", + "start": 154.24, + "end": 155.48, + "confidence": 0.979 + }, + { + "text": "Mais", + "start": 155.48, + "end": 155.82, + "confidence": 0.56 + }, + { + "text": "pourquoi", + "start": 155.82, + "end": 156.32, + "confidence": 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/dev/null +++ b/tests/expected/corner_cases.cpu/large_apollo11.mp3.words.json @@ -0,0 +1,2212 @@ +{ + "text": " Apollo 11, Houston, we got a recommendation for you on your Doige's EAs, LM EG EAs, over. Go ahead. We'd like to see it as a selected one or two on the helmet. We're gonna have it in B1, and you can put the other one on Mike's helmet, we're still seeing it. Okay. All right. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. We got some. Yeah, we're taking next day autumn to heal up. You won't hack me on this. You won't hack me on this. With a cover, I tried it already. Okay, fine. We weren't sure that this was a suggestion. We thought you could check it out. I'm not sure we've already done that. I guess, whatever you come up with, just let us know. Okay, no problem. 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Alright, okay, we like to say that they make the one that's on the helmet we're going to have in B1. And you can put the other one on the mic helmet with those GVA blizzard frames. Alright, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, 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Alright, okay, we like to say that they make the one that's on the helmet we're going to have in B1. And you can put the other one on the mic helmet with those GVA blizzard frames. Alright, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, 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diff --git a/tests/expected/corner_cases/arabic.mp3.words.json b/tests/expected/corner_cases/arabic.mp3.words.json new file mode 100644 index 0000000000000000000000000000000000000000..f88ce5e8e84ed6fbfd0acd935f21544d17bd4c95 --- /dev/null +++ b/tests/expected/corner_cases/arabic.mp3.words.json @@ -0,0 +1,393 @@ +{ + "text": " حبّي أنصار الهدى حبّي ركب الفدا وطلّبي سأر الشاهد وطلّبي سأر الشاهد لمتى سنضل رقودا نغرق في النوم ونشخر وعن الآذان نسمّه ونغمّض كي لا نمسر", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 1.8, + "end": 7.48, + "text": " حبّي أنصار الهدى", + "tokens": [ + 50364, + 11331, + 3555, + 11703, + 1829, + 14739, + 9381, + 9640, + 2423, + 3224, + 3215, + 7578, + 50714 + ], + "temperature": 0.0, + "avg_logprob": -0.5114130362486228, + "compression_ratio": 1.1842105263157894, + "no_speech_prob": 0.7993651032447815, + "confidence": 0.651, + "words": [ + { + "text": "حبّي", + "start": 1.8, + "end": 4.26, + "confidence": 0.436 + }, + { + "text": "أنصار", + "start": 4.26, + "end": 5.7, + "confidence": 0.795 + }, + { + "text": "الهدى", + "start": 5.7, + "end": 7.48, + "confidence": 0.837 + } + ] + }, + { + "id": 1, + "seek": 0, + "start": 9.24, + "end": 15.2, + "text": " حبّي ركب الفدا", + "tokens": [ + 50714, + 11331, + 3555, + 11703, + 1829, + 12602, + 4117, + 3555, + 27188, + 28259, + 51114 + ], + "temperature": 0.0, + "avg_logprob": -0.5114130362486228, + "compression_ratio": 1.1842105263157894, + "no_speech_prob": 0.7993651032447815, + "confidence": 0.829, + "words": [ + { + "text": "حبّي", + "start": 9.24, + "end": 12.58, + "confidence": 0.875 + }, + { + "text": "ركب", + "start": 12.58, + "end": 13.76, + "confidence": 0.853 + }, + { + "text": "الفدا", + "start": 13.76, + "end": 15.2, + "confidence": 0.711 + } + ] + }, + { + "id": 2, + "seek": 0, + "start": 18.86, + "end": 23.42, + "text": " وطلّبي سأر الشاهد", + "tokens": [ + 51114, + 4032, + 9566, + 1211, + 11703, + 21292, + 8608, + 10721, + 2288, + 25124, + 40294, + 3215, + 51514 + ], + 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Alright, okay, we like to say that they make the one that's on the helmet we're going to have in B1. And you can put the other one on the mic helmet with those GVA blizzard frames. Alright, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, 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got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.52, + "end": 6.54, + "text": " Apollo 11, Houston we got a recommendation for you on your Soyuz-VA GLEME GVA.", + "tokens": [ + 50364, + 25187, + 2975, + 11, + 18717, + 321, + 658, + 257, + 11879, + 337, + 291, + 322, + 428, + 24758, + 3334, + 12, + 20914, + 460, + 2634, + 15454, + 460, + 20914, + 13, + 50714 + ], + "temperature": 0.0, + "avg_logprob": -0.7220700916491056, + "compression_ratio": 1.39247311827957, + "no_speech_prob": 0.44993358850479126, + "confidence": 0.541, + "words": [ + { + "text": "Apollo", + "start": 0.52, + "end": 0.88, + "confidence": 0.156 + }, + { + "text": "11,", + "start": 0.88, + "end": 1.26, + "confidence": 0.977 + }, + { + "text": "Houston", + "start": 1.52, + "end": 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Ce qui fait la force du smartphone, c'est pas seulement l'accumulation des fonctions, mais la manière dont elles interagissent entre elles. Ce qui dit d'ailleurs sur la photo, c'est hyper convaincant. Alors évidemment, il faudrait ajouter les interfaces. L'écran tactile a été beaucoup très souvent mentionné. Mais bon, il faut dire qu'il profite aussi de 20 ans pendant lesquels les ordinateurs nous ont appris à cliquer sur des icônes. Sauf que le smartphone ajoute le toucher, ce qui rend le contact plus direct, plus sensible. Et puis évidemment, il faudrait parler aussi des applications qui permettent de contourner le côté touffu de la navigation web pour aller directement au but. Bref, tout ça, ce sont les conditions qui permettent de créer cet objet dont Nicolas dit qu'il est vraisemblablement inédit dans l'histoire de l'humanité. Mais ça, ça soulève une autre interrogation. Est-ce que le fait que cet objet soit inédit induit que notre rapport à lui est aussi un rapport inédit? Je veux dire, est-ce que le rapport qu'on a au smartphone est comparable à celui qu'on entretenait à d'autres objets techniques comme la voiture ou le téléphone? Il n'y a pas d'équivalent en fait. Et donc cette espèce de nouveauté dans la relation à l'objet, c'est fascinant et terrifiant. Parce qu'on a l'impression, comme le disent les utilisateurs et les services, d'être dépendants de cet objet, d'induire en fait une espèce de relation, de médiation avec le monde qui rend de l'ampleur et qui amène aussi à des formes de rejet. Donc, à objet inédit, rapport inédit. Et ce rapport, si j'en crois Nicolas, serait caractérisé par un mélange de dépendance et de rejet. Bon, en vrai, il faudrait remonter très très finement toute l'histoire des objets techniques et de leur insertion dans nos vies pour déterminer si ce rapport est totalement inédit. Mais j'ai l'impression comme ça que Nicolas ne se trompe pas vraiment. Pour autant que je sache, il y a eu plein de discussions autour de la voiture ou même du téléphone. Mais la dépendance n'était pas du même ordre. Donc le rejet non plus n'était pas du même ordre. On peut adorer sa bagnole, en avoir besoin pour plein de choses. Et bien, le soir, quand on va se coucher, on la laisse. On ne l'a pas dans la main quand on est au lit, on ne l'emmène pas au chiottes. On pouvait être énervé par son môme qui occupait la ligne de téléphone pendant une heure chaque soir pour discuter avec un copain. Mais ça ne ressemblait pas à ce qu'on peut ressentir à voir ce même môme aujourd'hui, continuellement avec son smartphone dans la main, comme si c'était une sorte de pacemaker externe, comme si le lâcher allait entraîner sa mort immédiate. Bon, je dis ça pour le môme, mais c'est évidemment valable pour nous aussi. Donc, rapport inédit. D'accord. Mais pourquoi a-t-on l'impression qu'on n'en sortira jamais? Est-ce qu'il faut en remettre la faute sur les gens qui ont créé cet outil merveilleux et diabolique, et diabolique parce que merveilleux? Les économistes parlent de dépendance du sentier. C'est l'idée qu'on est sur un sentier qui a été établi, soit volontairement en marchant dessus, soit en définissant des bornes, en définissant une signalétique.", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.38, + "end": 3.62, + "text": " C'est évident ce que dit Nicolas, mais je ne me l'étais jamais formulé comme ça.", + "tokens": [ + 383, + 6, + 377, + 20090, + 1078, + 1769, + 631, + 6176, + 38268, + 11, + 2420, + 1506, + 408, + 385, + 287, + 6, + 22824, + 14540, + 49990, + 526, + 5173, + 2788, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.23666970461409614, + "compression_ratio": 1.6238532110091743, + "no_speech_prob": 0.1567964404821396, + "confidence": 0.935, + "words": [ + { + "text": "C'est", + "start": 0.38, + "end": 0.58, + "confidence": 0.961 + }, + { + "text": "évident", + "start": 0.58, + "end": 0.88, + "confidence": 0.984 + }, + { + "text": "ce", + "start": 0.88, + "end": 1.02, + "confidence": 0.663 + }, + { + "text": "que", + "start": 1.02, + "end": 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"end": 42.06, + "confidence": 0.998 + }, + { + "text": "cet", + "start": 42.06, + "end": 42.38, + "confidence": 0.998 + }, + { + "text": "objet", + "start": 42.38, + "end": 42.6, + "confidence": 0.994 + }, + { + "text": "dont", + "start": 42.6, + "end": 42.8, + "confidence": 0.779 + }, + { + "text": "Nicolas", + "start": 42.8, + "end": 43.26, + "confidence": 0.989 + }, + { + "text": "dit", + "start": 43.26, + "end": 43.5, + "confidence": 0.986 + }, + { + "text": "qu'il", + "start": 43.5, + "end": 43.7, + "confidence": 0.983 + }, + { + "text": "est", + "start": 43.7, + "end": 43.88, + "confidence": 0.991 + }, + { + "text": "vraisemblablement", + "start": 43.88, + "end": 44.98, + "confidence": 0.991 + }, + { + "text": "inédit", + "start": 44.98, + "end": 45.38, + "confidence": 0.98 + }, + { + "text": "dans", + "start": 45.38, + "end": 45.7, + "confidence": 0.969 + }, + { + "text": "l'histoire", + "start": 45.7, + "end": 45.98, + "confidence": 0.957 + }, + { + "text": "de", + "start": 45.98, + "end": 46.18, + "confidence": 0.999 + }, + { + "text": "l'humanité.", + "start": 46.18, + "end": 46.54, + "confidence": 0.992 + } + ] + }, + { + "id": 10, + "seek": 2534, + "start": 46.54, + "end": 48.82, + "text": " Mais ça, ça soulève une autre interrogation.", + "tokens": [ + 6313, + 2788, + 11, + 2788, + 5133, + 31397, + 2251, + 15081, + 24871, + 399, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.07915337880452473, + "compression_ratio": 1.6254416961130742, + "no_speech_prob": 3.457161710684886e-06, + "confidence": 0.969, + "words": [ + { + "text": "Mais", + "start": 46.54, + "end": 47.24, + "confidence": 0.846 + }, + { + "text": "ça,", + "start": 47.24, + "end": 47.72, + "confidence": 0.935 + }, + { + "text": "ça", + "start": 47.72, + "end": 47.76, + "confidence": 0.977 + }, + { + "text": "soulève", + "start": 47.76, + "end": 47.84, + "confidence": 0.993 + }, + { + "text": "une", + "start": 47.84, + "end": 48.02, + "confidence": 0.998 + }, + { + "text": "autre", + "start": 48.02, + "end": 48.26, + "confidence": 0.999 + }, + { + "text": "interrogation.", + "start": 48.26, + "end": 48.82, + "confidence": 0.997 + } + ] + }, + { + "id": 11, + "seek": 4884, + "start": 49.22, + "end": 55.46, + "text": " Est-ce que le fait que cet objet soit inédit induit que notre rapport à lui est aussi un rapport inédit?", + "tokens": [ + 4410, + 12, + 384, + 631, + 476, + 3887, + 631, + 8603, + 14964, + 12703, + 294, + 7811, + 270, + 13716, + 270, + 631, + 10349, + 18018, + 1531, + 8783, + 871, + 6212, + 517, + 18018, + 294, + 7811, + 270, + 2506 + ], + "temperature": 0.0, + "avg_logprob": -0.10746372298689078, + "compression_ratio": 1.662379421221865, + "no_speech_prob": 1.3105129255563952e-05, + "confidence": 0.988, + "words": [ + { + "text": "Est-ce", + "start": 49.22, + "end": 49.62, + "confidence": 0.982 + }, + { + "text": "que", + "start": 49.62, + "end": 49.72, + "confidence": 0.991 + }, + { + "text": "le", + "start": 49.72, + "end": 49.82, + "confidence": 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+ { + "text": "smartphone", + "start": 57.28, + "end": 57.6, + "confidence": 0.994 + }, + { + "text": "est", + "start": 57.6, + "end": 57.92, + "confidence": 0.95 + }, + { + "text": "comparable", + "start": 57.92, + "end": 58.24, + "confidence": 0.997 + }, + { + "text": "à", + "start": 58.24, + "end": 58.48, + "confidence": 0.949 + }, + { + "text": "celui", + "start": 58.48, + "end": 58.66, + "confidence": 0.998 + }, + { + "text": "qu'on", + "start": 58.66, + "end": 58.9, + "confidence": 0.989 + }, + { + "text": "entretenait", + "start": 58.9, + "end": 59.32, + "confidence": 0.929 + }, + { + "text": "à", + "start": 59.32, + "end": 59.46, + "confidence": 0.958 + }, + { + "text": "d'autres", + "start": 59.46, + "end": 59.7, + "confidence": 0.997 + }, + { + "text": "objets", + "start": 59.7, + "end": 59.96, + "confidence": 0.991 + }, + { + "text": "techniques", + "start": 59.96, + "end": 60.46, + "confidence": 0.983 + }, + { + "text": "comme", + "start": 60.46, + "end": 60.88, + "confidence": 0.587 + }, + { + "text": "la", + "start": 60.88, + "end": 61.5, + "confidence": 0.987 + }, + { + "text": "voiture", + "start": 61.5, + "end": 62.06, + "confidence": 1.0 + }, + { + "text": "ou", + "start": 62.06, + "end": 62.36, + "confidence": 0.945 + }, + { + "text": "le", + "start": 62.36, + "end": 62.68, + "confidence": 0.998 + }, + { + "text": "téléphone?", + "start": 62.68, + "end": 63.12, + "confidence": 0.999 + } + ] + }, + { + "id": 13, + "seek": 4884, + "start": 63.36, + "end": 66.66, + "text": " Il n'y a pas d'équivalent en fait.", + "tokens": [ + 4416, + 297, + 6, + 88, + 257, + 1736, + 274, + 6, + 20183, + 3576, + 317, + 465, + 3887, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.10746372298689078, + "compression_ratio": 1.662379421221865, + "no_speech_prob": 1.3105129255563952e-05, + "confidence": 0.936, + "words": [ + { + "text": "Il", + "start": 63.36, + "end": 65.42, + "confidence": 0.779 + }, + { + "text": "n'y", + "start": 65.42, + "end": 65.48, + 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"confidence": 0.766 + }, + { + "text": "dépendants", + "start": 75.42, + "end": 75.96, + "confidence": 0.789 + }, + { + "text": "de", + "start": 75.96, + "end": 76.08, + "confidence": 0.986 + }, + { + "text": "cet", + "start": 76.08, + "end": 76.26, + "confidence": 0.996 + }, + { + "text": "objet,", + "start": 76.26, + "end": 76.48, + "confidence": 0.996 + } + ] + }, + { + "id": 16, + "seek": 7684, + "start": 76.86, + "end": 83.26, + "text": " d'induire en fait une espèce de relation, de médiation avec le monde qui rend de l'ampleur et qui amène aussi à des formes de rejet.", + "tokens": [ + 274, + 6, + 471, + 43612, + 465, + 3887, + 2251, + 7089, + 30236, + 368, + 9721, + 11, + 368, + 42436, + 399, + 4163, + 476, + 10431, + 1956, + 6125, + 368, + 287, + 6, + 335, + 781, + 374, + 1030, + 1956, + 669, + 18832, + 6212, + 1531, + 730, + 1254, + 279, + 368, + 319, + 7108, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.06937986261704389, + "compression_ratio": 1.6787003610108304, + 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"text": "de", + "start": 82.9, + "end": 83.02, + "confidence": 0.998 + }, + { + "text": "rejet.", + "start": 83.02, + "end": 83.26, + "confidence": 0.883 + } + ] + }, + { + "id": 17, + "seek": 7684, + "start": 83.94, + "end": 87.8, + "text": " Donc, à objet inédit, rapport inédit.", + "tokens": [ + 7477, + 11, + 1531, + 14964, + 294, + 7811, + 270, + 11, + 18018, + 294, + 7811, + 270, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.06937986261704389, + "compression_ratio": 1.6787003610108304, + "no_speech_prob": 5.948771558905719e-06, + "confidence": 0.962, + "words": [ + { + "text": "Donc,", + "start": 83.94, + "end": 84.94, + "confidence": 0.971 + }, + { + "text": "à", + "start": 84.94, + "end": 84.98, + "confidence": 0.88 + }, + { + "text": "objet", + "start": 84.98, + "end": 85.36, + "confidence": 0.828 + }, + { + "text": "inédit,", + "start": 85.36, + "end": 86.56, + "confidence": 0.993 + }, + { + "text": "rapport", + "start": 86.56, + "end": 87.0, + "confidence": 0.981 + }, + { + "text": "inédit.", + "start": 87.0, + "end": 87.8, + "confidence": 0.998 + } + ] + }, + { + "id": 18, + "seek": 7684, + "start": 88.02, + "end": 95.14, + "text": " Et ce rapport, si j'en crois Nicolas, serait caractérisé par un mélange de dépendance et de rejet.", + "tokens": [ + 3790, + 1769, + 18018, + 11, + 1511, + 361, + 6, + 268, + 21724, + 38268, + 11, + 23139, + 1032, + 578, + 4198, + 22118, + 971, + 517, + 41953, + 933, + 368, + 45768, + 719, + 1030, + 368, + 319, + 7108, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.06937986261704389, + "compression_ratio": 1.6787003610108304, + "no_speech_prob": 5.948771558905719e-06, + "confidence": 0.972, + "words": [ + { + "text": "Et", + "start": 88.02, + "end": 88.48, + "confidence": 0.992 + }, + { + "text": "ce", + "start": 88.48, + "end": 88.86, + "confidence": 0.975 + }, + { + "text": "rapport,", + "start": 88.86, + "end": 89.28, + "confidence": 0.998 + }, + { + "text": "si", + "start": 89.28, + "end": 89.56, + "confidence": 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Donc le rejet non plus n'était pas du même ordre.", + "tokens": [ + 6313, + 635, + 45768, + 719, + 297, + 6, + 9743, + 1736, + 1581, + 5698, + 4792, + 265, + 13, + 7477, + 476, + 319, + 7108, + 2107, + 1804, + 297, + 6, + 9743, + 1736, + 1581, + 5698, + 4792, + 265, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.07386374800172571, + "compression_ratio": 1.685512367491166, + "no_speech_prob": 5.46344235772267e-05, + "confidence": 0.972, + "words": [ + { + "text": "Mais", + "start": 115.34, + "end": 115.72, + "confidence": 0.994 + }, + { + "text": "la", + "start": 115.72, + "end": 116.02, + "confidence": 0.937 + }, + { + "text": "dépendance", + "start": 116.02, + "end": 116.4, + "confidence": 0.997 + }, + { + "text": "n'était", + "start": 116.4, + "end": 116.62, + "confidence": 0.994 + }, + { + "text": "pas", + "start": 116.62, + "end": 117.0, + "confidence": 0.998 + }, + { + "text": "du", + "start": 117.0, + "end": 117.16, + "confidence": 0.995 + }, + { + "text": "même", + "start": 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"id": 24, + "seek": 10584, + "start": 119.98, + "end": 123.02, + "text": " On peut adorer sa bagnole, en avoir besoin pour plein de choses.", + "tokens": [ + 1282, + 5977, + 614, + 17618, + 601, + 3411, + 1771, + 306, + 11, + 465, + 10853, + 19207, + 2016, + 21088, + 368, + 14488, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.07386374800172571, + "compression_ratio": 1.685512367491166, + "no_speech_prob": 5.46344235772267e-05, + "confidence": 0.991, + "words": [ + { + "text": "On", + "start": 119.98, + "end": 120.18, + "confidence": 0.996 + }, + { + "text": "peut", + "start": 120.18, + "end": 120.38, + "confidence": 0.997 + }, + { + "text": "adorer", + "start": 120.38, + "end": 120.66, + "confidence": 0.99 + }, + { + "text": "sa", + "start": 120.66, + "end": 120.88, + "confidence": 0.985 + }, + { + "text": "bagnole,", + "start": 120.88, + "end": 121.46, + "confidence": 0.984 + }, + { + "text": "en", + "start": 121.46, + "end": 121.56, + "confidence": 0.989 + }, + { + "text": "avoir", + "start": 121.56, + "end": 121.74, + "confidence": 0.998 + }, + { + "text": "besoin", + "start": 121.74, + "end": 122.1, + "confidence": 0.999 + }, + { + "text": "pour", + "start": 122.1, + "end": 122.34, + "confidence": 0.987 + }, + { + "text": "plein", + "start": 122.34, + "end": 122.68, + "confidence": 0.989 + }, + { + "text": "de", + "start": 122.68, + "end": 122.8, + "confidence": 0.998 + }, + { + "text": "choses.", + "start": 122.8, + "end": 123.02, + "confidence": 0.989 + } + ] + }, + { + "id": 25, + "seek": 10584, + "start": 123.28, + "end": 126.36, + "text": " Et bien, le soir, quand on va se coucher, on la laisse.", + "tokens": [ + 3790, + 3610, + 11, + 476, + 27105, + 11, + 6932, + 322, + 2773, + 369, + 1384, + 6759, + 11, + 322, + 635, + 30969, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.07386374800172571, + "compression_ratio": 1.685512367491166, + "no_speech_prob": 5.46344235772267e-05, + "confidence": 0.895, + "words": [ + { + "text": "Et", + "start": 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26, + "seek": 10584, + "start": 126.98, + "end": 130.48, + "text": " On ne l'a pas dans la main quand on est au lit, on ne l'emmène pas au chiottes.", + "tokens": [ + 1282, + 408, + 287, + 6, + 64, + 1736, + 2680, + 635, + 2135, + 6932, + 322, + 871, + 1609, + 7997, + 11, + 322, + 408, + 287, + 6, + 443, + 76, + 18832, + 1736, + 1609, + 13228, + 1521, + 279, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.07386374800172571, + "compression_ratio": 1.685512367491166, + "no_speech_prob": 5.46344235772267e-05, + "confidence": 0.914, + "words": [ + { + "text": "On", + "start": 126.98, + "end": 127.32, + "confidence": 0.954 + }, + { + "text": "ne", + "start": 127.32, + "end": 127.36, + "confidence": 0.803 + }, + { + "text": "l'a", + "start": 127.36, + "end": 127.48, + "confidence": 0.974 + }, + { + "text": "pas", + "start": 127.48, + "end": 127.68, + "confidence": 0.999 + }, + { + "text": "dans", + "start": 127.68, + "end": 127.8, + "confidence": 0.996 + }, + { + "text": "la", + "start": 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"chiottes.", + "start": 129.86, + "end": 130.48, + "confidence": 0.828 + } + ] + }, + { + "id": 27, + "seek": 13084, + "start": 130.86, + "end": 136.9, + "text": " On pouvait être énervé par son môme qui occupait la ligne de téléphone pendant une heure chaque soir pour discuter avec un copain.", + "tokens": [ + 1282, + 45913, + 7418, + 45045, + 15797, + 971, + 1872, + 275, + 2851, + 1398, + 1956, + 8073, + 1001, + 635, + 34207, + 368, + 47159, + 17338, + 2251, + 30027, + 18920, + 27105, + 2016, + 2983, + 20314, + 4163, + 517, + 2971, + 491, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.06199159333200166, + "compression_ratio": 1.6127167630057804, + "no_speech_prob": 1.6126719856401905e-05, + "confidence": 0.955, + "words": [ + { + "text": "On", + "start": 130.86, + "end": 131.04, + "confidence": 0.983 + }, + { + "text": "pouvait", + "start": 131.04, + "end": 131.28, + "confidence": 0.989 + }, + { + "text": "être", + "start": 131.28, + "end": 131.48, + "confidence": 0.996 + }, + { 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"confidence": 0.975 + }, + { + "text": "c'était", + "start": 144.64, + "end": 144.82, + "confidence": 0.991 + }, + { + "text": "une", + "start": 144.82, + "end": 145.06, + "confidence": 0.989 + }, + { + "text": "sorte", + "start": 145.06, + "end": 145.22, + "confidence": 0.997 + }, + { + "text": "de", + "start": 145.22, + "end": 145.3, + "confidence": 0.982 + }, + { + "text": "pacemaker", + "start": 145.3, + "end": 145.82, + "confidence": 0.917 + }, + { + "text": "externe,", + "start": 145.82, + "end": 146.3, + "confidence": 0.992 + } + ] + }, + { + "id": 30, + "seek": 13084, + "start": 146.34, + "end": 148.84, + "text": " comme si le lâcher allait entraîner sa mort immédiate.", + "tokens": [ + 5173, + 1511, + 476, + 48835, + 6759, + 439, + 1001, + 22284, + 7517, + 1193, + 601, + 6599, + 3397, + 526, + 4504, + 473, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.06199159333200166, + "compression_ratio": 1.6127167630057804, + "no_speech_prob": 1.6126719856401905e-05, + "confidence": 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+ { + "text": "c'est", + "start": 150.52, + "end": 150.82, + "confidence": 0.981 + }, + { + "text": "évidemment", + "start": 150.82, + "end": 151.14, + "confidence": 0.98 + }, + { + "text": "valable", + "start": 151.14, + "end": 151.48, + "confidence": 0.998 + }, + { + "text": "pour", + "start": 151.48, + "end": 151.62, + "confidence": 0.997 + }, + { + "text": "nous", + "start": 151.62, + "end": 151.76, + "confidence": 0.999 + }, + { + "text": "aussi.", + "start": 151.76, + "end": 151.96, + "confidence": 0.996 + } + ] + }, + { + "id": 32, + "seek": 13084, + "start": 152.34, + "end": 158.22, + "text": " Donc, rapport inédit. D'accord. Mais pourquoi a-t-on l'impression qu'on n'en sortira jamais?", + "tokens": [ + 7477, + 11, + 18018, + 294, + 7811, + 270, + 13, + 413, + 6, + 19947, + 13, + 6313, + 19934, + 257, + 12, + 83, + 12, + 266, + 287, + 6, + 36107, + 421, + 6, + 266, + 297, + 6, + 268, + 1333, + 4271, + 14540, + 2506 + ], + "temperature": 0.0, + "avg_logprob": -0.06199159333200166, + "compression_ratio": 1.6127167630057804, + "no_speech_prob": 1.6126719856401905e-05, + "confidence": 0.948, + "words": [ + { + "text": "Donc,", + "start": 152.34, + "end": 153.46, + "confidence": 0.991 + }, + { + "text": "rapport", + "start": 153.46, + "end": 153.66, + "confidence": 0.976 + }, + { + "text": "inédit.", + "start": 153.66, + "end": 154.24, + "confidence": 0.996 + }, + { + "text": "D'accord.", + "start": 154.24, + "end": 155.48, + "confidence": 0.978 + }, + { + "text": "Mais", + "start": 155.48, + "end": 155.82, + "confidence": 0.557 + }, + { + "text": "pourquoi", + "start": 155.82, + "end": 156.32, + "confidence": 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Ce qui fait la force du smartphone, c'est pas seulement l'accumulation des fonctions, mais la manière dont elles interagissent entre elles. Ce qui dit d'ailleurs sur la photo, c'est hyper convaincant. Alors évidemment, il faudrait ajouter les interfaces. L'écran tactile a été beaucoup très souvent mentionné. Mais bon, il faut dire qu'il profite aussi de 20 ans pendant lesquels les ordinateurs nous ont appris à cliquer sur des icônes. Sauf que le smartphone ajoute le toucher, ce qui rend le contact plus direct, plus sensible. Et puis évidemment, il faudrait parler aussi des applications qui permettent de contourner le côté touffu de la navigation web pour aller directement au but. Bref, tout ça, ce sont les conditions qui permettent de créer cet objet dont Nicolas dit qu'il est vraisemblablement inédit dans l'histoire de l'humanité. Mais ça, ça soulève une autre interrogation. Est-ce que le fait que cet objet soit inédit induit que notre rapport à lui est aussi un rapport inédit ? Je veux dire, est-ce que le rapport qu'on a au smartphone est comparable à celui qu'on entretenait à d'autres objets techniques comme la voiture ou le téléphone ? Il n'y a pas d'équivalent en fait. Et donc cette espèce de nouveauté dans la relation à l'objet, c'est fascinant et terrifiant. Parce qu'on a l'impression, comme le disent les utilisateurs et les services, d'être dépendant de cet objet, d'induire en fait une espèce de relation, de médiation avec le monde qui rend de l'ampleur et qui amène aussi à des formes de rejet. Donc à objet inédit, rapport inédit. Et ce rapport, si j'en crois à Nicolas, serait caractérisé par un mélange de dépendance et de rejet. Bon, en vrai, il faudrait remonter très très finement toute l'histoire des objets techniques et de leur insertion dans nos vies pour déterminer si ce rapport est totalement inédit. Mais j'ai l'impression comme ça que Nicolas ne se trompe pas vraiment. Pour autant que je sache, il y a eu plein de discussions autour de la voiture ou même du téléphone. Mais la dépendance n'était pas du même ordre. Donc le rejet non plus n'était pas du même ordre. On peut adorer sa bagnole, en avoir besoin pour plein de choses. Le soir, quand on va se coucher, on la laisse. On ne l'a pas dans la main quand on est au lit, on ne l'emmène pas au chiottes. On pouvait être énervé par son môme qui occupait la ligne de téléphone pendant une heure chaque soir pour discuter avec un copain. Mais ça ne ressemblait pas à ce qu'on peut ressentir à voir ce même môme aujourd'hui, continuellement avec son smartphone dans la main, comme si c'était une sorte de pacemaker externe, comme si le lâcher allait entraîner sa mort immédiate. Bon, je dis ça pour le môme, mais c'est évidemment valable pour nous aussi. Donc, rapport inédit, d'accord. Mais pourquoi a-t-on l'impression qu'on n'en sortira jamais ? Est-ce qu'il faut en remettre la faute sur les gens qui ont créé cet outil merveilleux et diabolique, et diabolique parce que merveilleux ? Les économistes parlent de dépendance du sentier. C'est l'idée qu'on met sur un sentier qui a été établi, soit volontairement en marchant dessus, soit en définissant des bornes, en définissant une signalétique.", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.4, + "end": 3.66, + "text": " C'est évident ce que dit Nicolas, mais je ne me l'étais jamais formulé comme ça.", + "tokens": [ + 50364, + 383, + 6, + 377, + 20090, + 1078, + 1769, + 631, + 6176, + 38268, + 11, + 2420, + 1506, + 408, + 385, + 287, + 6, + 22824, + 14540, + 49990, + 526, + 5173, + 2788, + 13, + 50539 + ], + "temperature": 0.0, + "avg_logprob": -0.23621009675082782, + "compression_ratio": 1.6238532110091743, + "no_speech_prob": 0.1557241678237915, + "confidence": 0.935, + "words": [ + { + "text": "C'est", + "start": 0.4, + "end": 0.64, + "confidence": 0.961 + }, + { + "text": "évident", + "start": 0.64, + "end": 0.9, + "confidence": 0.984 + }, + { + "text": "ce", + "start": 0.9, + "end": 1.0, + "confidence": 0.663 + }, + { + "text": "que", + "start": 1.0, + 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"end": 82.62, + "confidence": 0.959 + }, + { + "text": "des", + "start": 82.62, + "end": 82.7, + "confidence": 0.992 + }, + { + "text": "formes", + "start": 82.7, + "end": 82.88, + "confidence": 0.995 + }, + { + "text": "de", + "start": 82.88, + "end": 83.04, + "confidence": 0.998 + }, + { + "text": "rejet.", + "start": 83.04, + "end": 83.3, + "confidence": 0.802 + } + ] + }, + { + "id": 17, + "seek": 7134, + "start": 83.92, + "end": 87.7, + "text": " Donc à objet inédit, rapport inédit.", + "tokens": [ + 50989, + 7477, + 1531, + 14964, + 294, + 7811, + 270, + 11, + 18018, + 294, + 7811, + 270, + 13, + 51189 + ], + "temperature": 0.0, + "avg_logprob": -0.11261525396573341, + "compression_ratio": 1.5975609756097562, + "no_speech_prob": 0.015181636437773705, + "confidence": 0.901, + "words": [ + { + "text": "Donc", + "start": 83.92, + "end": 84.46, + "confidence": 0.984 + }, + { + "text": "à", + "start": 84.46, + "end": 84.98, + "confidence": 0.481 + }, + { + "text": "objet", + "start": 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déterminer si ce rapport est totalement inédit.", + "tokens": [ + 50739, + 2016, + 2795, + 29725, + 260, + 1511, + 1769, + 18018, + 871, + 45203, + 294, + 7811, + 270, + 13, + 50889 + ], + "temperature": 0.0, + "avg_logprob": -0.07804971811722736, + "compression_ratio": 1.6719745222929936, + "no_speech_prob": 0.017434893175959587, + "confidence": 0.995, + "words": [ + { + "text": "pour", + "start": 102.86, + "end": 103.1, + "confidence": 0.989 + }, + { + "text": "déterminer", + "start": 103.1, + "end": 103.64, + "confidence": 0.995 + }, + { + "text": "si", + "start": 103.64, + "end": 103.76, + "confidence": 0.986 + }, + { + "text": "ce", + "start": 103.76, + "end": 103.94, + "confidence": 0.991 + }, + { + "text": "rapport", + "start": 103.94, + "end": 104.26, + "confidence": 0.998 + }, + { + "text": "est", + "start": 104.26, + "end": 104.84, + "confidence": 0.997 + }, + { + "text": "totalement", + "start": 104.84, + "end": 105.3, + "confidence": 0.998 + }, + { + "text": "inédit.", + 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pas du même ordre.", + "tokens": [ + 51389, + 6313, + 635, + 45768, + 719, + 297, + 6, + 9743, + 1736, + 1581, + 5698, + 4792, + 265, + 13, + 51489 + ], + "temperature": 0.0, + "avg_logprob": -0.07804971811722736, + "compression_ratio": 1.6719745222929936, + "no_speech_prob": 0.017434893175959587, + "confidence": 0.992, + "words": [ + { + "text": "Mais", + "start": 115.48, + "end": 115.78, + "confidence": 0.993 + }, + { + "text": "la", + "start": 115.78, + "end": 116.04, + "confidence": 0.944 + }, + { + "text": "dépendance", + "start": 116.04, + "end": 116.42, + "confidence": 0.996 + }, + { + "text": "n'était", + "start": 116.42, + "end": 116.7, + "confidence": 0.994 + }, + { + "text": "pas", + "start": 116.7, + "end": 117.0, + "confidence": 0.998 + }, + { + "text": "du", + "start": 117.0, + "end": 117.2, + "confidence": 0.996 + }, + { + "text": "même", + "start": 117.2, + "end": 117.44, + "confidence": 0.998 + }, + { + "text": "ordre.", + "start": 117.44, + "end": 117.7, + 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" Mais ça ne ressemblait pas à ce qu'on peut ressentir à voir ce même môme aujourd'hui,", + "tokens": [ + 51039, + 6313, + 2788, + 408, + 725, + 15750, + 35235, + 1736, + 1531, + 1769, + 421, + 6, + 266, + 5977, + 24689, + 317, + 347, + 1531, + 10695, + 1769, + 5698, + 275, + 2851, + 1398, + 14023, + 6, + 10556, + 11, + 51289 + ], + "temperature": 0.0, + "avg_logprob": -0.08259125505940298, + "compression_ratio": 1.6818181818181819, + "no_speech_prob": 0.011154274456202984, + "confidence": 0.956, + "words": [ + { + "text": "Mais", + "start": 137.26, + "end": 137.5, + "confidence": 0.989 + }, + { + "text": "ça", + "start": 137.5, + "end": 137.68, + "confidence": 0.927 + }, + { + "text": "ne", + "start": 137.68, + "end": 137.88, + "confidence": 0.999 + }, + { + "text": "ressemblait", + "start": 137.88, + "end": 138.42, + "confidence": 0.993 + }, + { + "text": "pas", + "start": 138.42, + "end": 138.78, + "confidence": 0.995 + }, + { + "text": "à", + "start": 138.78, + "end": 138.9, + 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smartphone dans la main,", + "tokens": [ + 51289, + 2354, + 285, + 1712, + 4163, + 1872, + 13307, + 2680, + 635, + 2135, + 11, + 51414 + ], + "temperature": 0.0, + "avg_logprob": -0.08259125505940298, + "compression_ratio": 1.6818181818181819, + "no_speech_prob": 0.011154274456202984, + "confidence": 0.961, + "words": [ + { + "text": "continuellement", + "start": 142.16, + "end": 142.94, + "confidence": 0.963 + }, + { + "text": "avec", + "start": 142.94, + "end": 143.2, + "confidence": 0.844 + }, + { + "text": "son", + "start": 143.2, + "end": 143.42, + "confidence": 0.994 + }, + { + "text": "smartphone", + "start": 143.42, + "end": 143.76, + "confidence": 0.972 + }, + { + "text": "dans", + "start": 143.76, + "end": 143.92, + "confidence": 0.964 + }, + { + "text": "la", + "start": 143.92, + "end": 144.02, + "confidence": 0.997 + }, + { + "text": "main,", + "start": 144.02, + "end": 144.22, + "confidence": 0.997 + } + ] + }, + { + "id": 31, + "seek": 12334, + "start": 144.34, + "end": 148.8, + "text": " comme si c'était une sorte de pacemaker externe, comme si le lâcher allait entraîner sa mort immédiate.", + "tokens": [ + 51414, + 5173, + 1511, + 269, + 6, + 9743, + 2251, + 25559, + 368, + 15165, + 49523, + 454, + 391, + 716, + 11, + 5173, + 1511, + 476, + 48835, + 6759, + 439, + 1001, + 22284, + 7517, + 1193, + 601, + 6599, + 3397, + 526, + 4504, + 473, + 13, + 51639 + ], + "temperature": 0.0, + "avg_logprob": -0.08259125505940298, + "compression_ratio": 1.6818181818181819, + "no_speech_prob": 0.011154274456202984, + "confidence": 0.973, + "words": [ + { + "text": "comme", + "start": 144.34, + "end": 144.56, + "confidence": 0.985 + }, + { + "text": "si", + "start": 144.56, + "end": 144.66, + "confidence": 0.972 + }, + { + "text": "c'était", + "start": 144.66, + "end": 144.86, + "confidence": 0.987 + }, + { + "text": "une", + "start": 144.86, + "end": 144.98, + "confidence": 0.983 + }, + { + "text": "sorte", + "start": 144.98, + "end": 145.14, + "confidence": 0.992 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/dev/null +++ b/tests/expected/medium_fr.cpu/radio_short.mp3.words.json @@ -0,0 +1,1977 @@ +{ + "text": " Le plus important au poker ce ne sont pas les cartes, c'est ce que vous en faites. Winamax, la référence du poker en ligne. Bonsoir à toutes et tous, vous êtes sur BFM TV, nous sommes en direct, c'est bien sûr BFM story avec tout ce qui fait l'actualité. Durant 60 minutes ce sont des gros plans, des analyses, des réactions que nous vous proposons. Comment Eric Verth peut-il encore soutenir la réforme des retraites alors qu'il est englué dans sa propre affaire, l'affaire Verth-Bettancourt? Question posée par les leaders de la CFDT et la CGT. Réponse de Nicolas Sarkozy, Eric Verth portera le débat sur les retraites, on en parle dans BFM story avec le numéro de la CFDT. Et puis il y a une bataille qui a démarré, celle entre Marine Le Pen et Bruno Gognich, la bataille de la succession de Jean-Marie Le Pen à la tête du Front National. La tournée de campagne de Marine Le Pen commence aujourd'hui dans le Var, Marine Le Pen sera en direct dans BFM story. Restez avec nous Marine Le Pen dans moins de 3 minutes, à tout de suite. Musique L'actualité c'est aussi aujourd'hui un dernier adieu, dernier adieu à Laurent Fignon, c'était au cimetière du Père Lachaise à Paris. L'ancien double vainqueur du Tour de France, vaincu par le cancer à 50 ans, a été incinéré en petit comité aujourd'hui.", + "segments": [ + { + "id": 0, + "seek": 3000, + "start": 30.86, + "end": 34.26, + "text": " Le plus important au poker ce ne sont pas les cartes, c'est ce que vous en faites.", + "tokens": [ + 1456, + 1804, + 1021, + 1609, + 36863, + 1769, + 408, + 4900, + 1736, + 1512, + 5467, + 279, + 11, + 269, + 6, + 377, + 1769, + 631, + 2630, + 465, + 29902, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.1935427300283842, + "compression_ratio": 1.5084745762711864, + "no_speech_prob": 0.5593915581703186, + "confidence": 0.92, + "words": [ + { + "text": "Le", + "start": 30.86, + "end": 31.02, + "confidence": 0.535 + }, + { + "text": "plus", + "start": 31.02, + "end": 31.12, + "confidence": 0.99 + }, + { + "text": "important", + "start": 31.12, + "end": 31.48, + "confidence": 0.993 + }, + { + "text": "au", + "start": 31.48, + "end": 31.64, + "confidence": 0.946 + }, + { + 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Ce qui fait la force du smartphone, c'est pas seulement l'accumulation des fonctions, mais la manière dont elles interagissent entre elles. Ce qui dit d'ailleurs sur la photo, c'est hyper convaincant. Alors évidemment, il faudrait ajouter les interfaces. L'écran tactile a été beaucoup très souvent mentionné. Mais bon, il faut dire qu'il profite aussi de 20 ans pendant lesquels les ordinateurs nous ont appris à cliquer sur des icônes. Sauf que le smartphone ajoute le toucher, ce qui rend le contact plus direct, plus sensible. Et puis évidemment, il faudrait parler aussi des applications qui permettent de contourner le côté touffu de la navigation web pour aller directement au but. Bref, tout ça, ce sont les conditions qui permettent de créer cet objet dont Nicolas dit qu'il est vraisemblablement inédit dans l'histoire de l'humanité. Mais ça, ça soulève une autre interrogation. Est-ce que le fait que cet objet soit inédit induit que notre rapport à lui est aussi un rapport inédit? Je veux dire, est-ce que le rapport qu'on a au smartphone est comparable à celui qu'on entretenait à d'autres objets techniques comme la voiture ou le téléphone? Il n'y a pas d'équivalent en fait. Et donc cette espèce de nouveauté dans la relation à l'objet, c'est fascinant et terrifiant. Parce qu'on a l'impression, comme le disent les utilisateurs et les services, d'être dépendants de cet objet, d'induire en fait une espèce de relation, de médiation avec le monde qui rend de l'ampleur et qui amène aussi à des formes de rejet. Donc, à objet inédit, rapport inédit. Et ce rapport, si j'en crois Nicolas, serait caractérisé par un mélange de dépendance et de rejet. Bon, en vrai, il faudrait remonter très très finement toute l'histoire des objets techniques et de leur insertion dans nos vies pour déterminer si ce rapport est totalement inédit. Mais j'ai l'impression comme ça que Nicolas ne se trompe pas vraiment. Pour autant que je sache, il y a eu plein de discussions autour de la voiture ou même du téléphone. Mais la dépendance n'était pas du même ordre. Donc le rejet non plus n'était pas du même ordre. On peut adorer sa bagnole, en avoir besoin pour plein de choses. Et bien, le soir, quand on va se coucher, on la laisse. On ne l'a pas dans la main quand on est au lit, on ne l'emmène pas au chiottes. On pouvait être énervé par son môme qui occupait la ligne de téléphone pendant une heure chaque soir pour discuter avec un copain. Mais ça ne ressemblait pas à ce qu'on peut ressentir à voir ce même môme aujourd'hui, continuellement avec son smartphone dans la main, comme si c'était une sorte de pacemaker externe, comme si le lâcher allait entraîner sa mort immédiate. Bon, je dis ça pour le môme, mais c'est évidemment valable pour nous aussi. Donc, rapport inédit. D'accord. Mais pourquoi a-t-on l'impression qu'on n'en sortira jamais? Est-ce qu'il faut en remettre la faute sur les gens qui ont créé cet outil merveilleux et diabolique, et diabolique parce que merveilleux? Les économistes parlent de dépendance du sentier. C'est l'idée qu'on est sur un sentier qui a été établi, soit volontairement en marchant dessus, soit en définissant des bornes, en définissant une signalétique.", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.38, + "end": 3.62, + "text": " C'est évident ce que dit Nicolas, mais je ne me l'étais jamais formulé comme ça.", + "tokens": [ + 383, + 6, + 377, + 20090, + 1078, + 1769, + 631, + 6176, + 38268, + 11, + 2420, + 1506, + 408, + 385, + 287, + 6, + 22824, + 14540, + 49990, + 526, + 5173, + 2788, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.23666970461409614, + "compression_ratio": 1.6238532110091743, + "no_speech_prob": 0.1567964404821396, + "confidence": 0.935, + "words": [ + { + "text": "C'est", + "start": 0.38, + "end": 0.58, + "confidence": 0.961 + }, + { + "text": "évident", + "start": 0.58, + "end": 0.88, + "confidence": 0.984 + }, + { + "text": "ce", + "start": 0.88, + "end": 1.02, + "confidence": 0.663 + }, + { + "text": "que", + "start": 1.02, + "end": 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16.02, + "text": " Alors évidemment, il faudrait ajouter les interfaces.", + "tokens": [ + 9946, + 24724, + 11, + 1930, + 38694, + 8645, + 17680, + 23985, + 1512, + 28416, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.23666970461409614, + "compression_ratio": 1.6238532110091743, + "no_speech_prob": 0.1567964404821396, + "confidence": 0.913, + "words": [ + { + "text": "Alors", + "start": 13.34, + "end": 13.62, + "confidence": 0.585 + }, + { + "text": "évidemment,", + "start": 13.62, + "end": 14.34, + "confidence": 0.832 + }, + { + "text": "il", + "start": 14.34, + "end": 14.38, + "confidence": 0.952 + }, + { + "text": "faudrait", + "start": 14.38, + "end": 14.74, + "confidence": 0.996 + }, + { + "text": "ajouter", + "start": 14.74, + "end": 15.16, + "confidence": 0.992 + }, + { + "text": "les", + "start": 15.16, + "end": 15.52, + "confidence": 0.985 + }, + { + "text": "interfaces.", + "start": 15.52, + "end": 16.02, + "confidence": 0.984 + } + ] + }, + { + "id": 5, + "seek": 0, + 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"mentionné.", + "start": 18.9, + "end": 19.36, + "confidence": 0.978 + } + ] + }, + { + "id": 6, + "seek": 0, + "start": 19.84, + "end": 25.26, + "text": " Mais bon, il faut dire qu'il profite aussi de 20 ans pendant lesquels les ordinateurs nous ont appris à cliquer sur des icônes.", + "tokens": [ + 6313, + 4428, + 11, + 1930, + 8487, + 1264, + 421, + 6, + 388, + 1740, + 642, + 6212, + 368, + 945, + 1567, + 17338, + 1512, + 358, + 1625, + 1512, + 4792, + 13923, + 2156, + 4666, + 6592, + 724, + 5714, + 1531, + 596, + 23909, + 1022, + 730, + 4376, + 2851, + 4081, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.23666970461409614, + "compression_ratio": 1.6238532110091743, + "no_speech_prob": 0.1567964404821396, + "confidence": 0.92, + "words": [ + { + "text": "Mais", + "start": 19.84, + "end": 20.22, + "confidence": 0.944 + }, + { + "text": "bon,", + "start": 20.22, + "end": 20.52, + "confidence": 0.667 + }, + { + "text": "il", + "start": 20.52, + "end": 20.6, + "confidence": 0.99 + 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45.98, + "end": 46.18, + "confidence": 0.999 + }, + { + "text": "l'humanité.", + "start": 46.18, + "end": 46.54, + "confidence": 0.992 + } + ] + }, + { + "id": 10, + "seek": 2534, + "start": 46.54, + "end": 48.82, + "text": " Mais ça, ça soulève une autre interrogation.", + "tokens": [ + 6313, + 2788, + 11, + 2788, + 5133, + 31397, + 2251, + 15081, + 24871, + 399, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.07915337880452473, + "compression_ratio": 1.6254416961130742, + "no_speech_prob": 3.457161710684886e-06, + "confidence": 0.969, + "words": [ + { + "text": "Mais", + "start": 46.54, + "end": 47.24, + "confidence": 0.846 + }, + { + "text": "ça,", + "start": 47.24, + "end": 47.72, + "confidence": 0.935 + }, + { + "text": "ça", + "start": 47.72, + "end": 47.76, + "confidence": 0.977 + }, + { + "text": "soulève", + "start": 47.76, + "end": 47.84, + "confidence": 0.993 + }, + { + "text": "une", + "start": 47.84, + "end": 48.02, + "confidence": 0.998 + }, + { + "text": "autre", + "start": 48.02, + "end": 48.26, + "confidence": 0.999 + }, + { + "text": "interrogation.", + "start": 48.26, + "end": 48.82, + "confidence": 0.997 + } + ] + }, + { + "id": 11, + "seek": 4884, + "start": 49.22, + "end": 55.46, + "text": " Est-ce que le fait que cet objet soit inédit induit que notre rapport à lui est aussi un rapport inédit?", + "tokens": [ + 4410, + 12, + 384, + 631, + 476, + 3887, + 631, + 8603, + 14964, + 12703, + 294, + 7811, + 270, + 13716, + 270, + 631, + 10349, + 18018, + 1531, + 8783, + 871, + 6212, + 517, + 18018, + 294, + 7811, + 270, + 2506 + ], + "temperature": 0.0, + "avg_logprob": -0.10746372298689078, + "compression_ratio": 1.662379421221865, + "no_speech_prob": 1.3105129255563952e-05, + "confidence": 0.988, + "words": [ + { + "text": "Est-ce", + "start": 49.22, + "end": 49.62, + "confidence": 0.982 + }, + { + "text": "que", + "start": 49.62, + "end": 49.72, + "confidence": 0.991 + }, + { + "text": "le", + "start": 49.72, + "end": 49.82, + "confidence": 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+ "start": 70.24, + "end": 70.38, + "confidence": 0.98 + }, + { + "text": "fascinant", + "start": 70.38, + "end": 70.64, + "confidence": 0.978 + }, + { + "text": "et", + "start": 70.64, + "end": 70.76, + "confidence": 0.964 + }, + { + "text": "terrifiant.", + "start": 70.76, + "end": 71.52, + "confidence": 0.977 + } + ] + }, + { + "id": 15, + "seek": 4884, + "start": 71.62, + "end": 76.48, + "text": " Parce qu'on a l'impression, comme le disent les utilisateurs et les services, d'être dépendants de cet objet,", + "tokens": [ + 20429, + 421, + 6, + 266, + 257, + 287, + 6, + 36107, + 11, + 5173, + 476, + 37313, + 1512, + 33643, + 25929, + 1030, + 1512, + 3328, + 11, + 274, + 6, + 9498, + 45768, + 1719, + 368, + 8603, + 14964, + 11 + ], + "temperature": 0.0, + "avg_logprob": -0.10746372298689078, + "compression_ratio": 1.662379421221865, + "no_speech_prob": 1.3105129255563952e-05, + "confidence": 0.813, + "words": [ + { + "text": "Parce", + "start": 71.62, + "end": 71.86, + "confidence": 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"confidence": 0.766 + }, + { + "text": "dépendants", + "start": 75.42, + "end": 75.96, + "confidence": 0.789 + }, + { + "text": "de", + "start": 75.96, + "end": 76.08, + "confidence": 0.986 + }, + { + "text": "cet", + "start": 76.08, + "end": 76.26, + "confidence": 0.996 + }, + { + "text": "objet,", + "start": 76.26, + "end": 76.48, + "confidence": 0.996 + } + ] + }, + { + "id": 16, + "seek": 7684, + "start": 76.86, + "end": 83.26, + "text": " d'induire en fait une espèce de relation, de médiation avec le monde qui rend de l'ampleur et qui amène aussi à des formes de rejet.", + "tokens": [ + 274, + 6, + 471, + 43612, + 465, + 3887, + 2251, + 7089, + 30236, + 368, + 9721, + 11, + 368, + 42436, + 399, + 4163, + 476, + 10431, + 1956, + 6125, + 368, + 287, + 6, + 335, + 781, + 374, + 1030, + 1956, + 669, + 18832, + 6212, + 1531, + 730, + 1254, + 279, + 368, + 319, + 7108, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.06937986261704389, + "compression_ratio": 1.6787003610108304, + 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+ "text": "monde", + "start": 79.92, + "end": 80.64, + "confidence": 0.992 + }, + { + "text": "qui", + "start": 80.64, + "end": 81.1, + "confidence": 0.696 + }, + { + "text": "rend", + "start": 81.1, + "end": 81.64, + "confidence": 0.91 + }, + { + "text": "de", + "start": 81.64, + "end": 81.78, + "confidence": 0.712 + }, + { + "text": "l'ampleur", + "start": 81.78, + "end": 82.02, + "confidence": 0.987 + }, + { + "text": "et", + "start": 82.02, + "end": 82.12, + "confidence": 0.931 + }, + { + "text": "qui", + "start": 82.12, + "end": 82.24, + "confidence": 0.976 + }, + { + "text": "amène", + "start": 82.24, + "end": 82.36, + "confidence": 0.973 + }, + { + "text": "aussi", + "start": 82.36, + "end": 82.56, + "confidence": 0.938 + }, + { + "text": "à", + "start": 82.56, + "end": 82.62, + "confidence": 0.941 + }, + { + "text": "des", + "start": 82.62, + "end": 82.72, + "confidence": 0.992 + }, + { + "text": "formes", + "start": 82.72, + "end": 82.9, + "confidence": 0.993 + }, + { + "text": "de", + "start": 82.9, + "end": 83.02, + "confidence": 0.998 + }, + { + "text": "rejet.", + "start": 83.02, + "end": 83.26, + "confidence": 0.883 + } + ] + }, + { + "id": 17, + "seek": 7684, + "start": 83.94, + "end": 87.8, + "text": " Donc, à objet inédit, rapport inédit.", + "tokens": [ + 7477, + 11, + 1531, + 14964, + 294, + 7811, + 270, + 11, + 18018, + 294, + 7811, + 270, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.06937986261704389, + "compression_ratio": 1.6787003610108304, + "no_speech_prob": 5.948771558905719e-06, + "confidence": 0.962, + "words": [ + { + "text": "Donc,", + "start": 83.94, + "end": 84.94, + "confidence": 0.971 + }, + { + "text": "à", + "start": 84.94, + "end": 84.98, + "confidence": 0.88 + }, + { + "text": "objet", + "start": 84.98, + "end": 85.36, + "confidence": 0.828 + }, + { + "text": "inédit,", + "start": 85.36, + "end": 86.56, + "confidence": 0.993 + }, + { + "text": "rapport", + "start": 86.56, + "end": 87.0, + "confidence": 0.981 + }, + { + "text": "inédit.", + "start": 87.0, + "end": 87.8, + "confidence": 0.998 + } + ] + }, + { + "id": 18, + "seek": 7684, + "start": 88.02, + "end": 95.14, + "text": " Et ce rapport, si j'en crois Nicolas, serait caractérisé par un mélange de dépendance et de rejet.", + "tokens": [ + 3790, + 1769, + 18018, + 11, + 1511, + 361, + 6, + 268, + 21724, + 38268, + 11, + 23139, + 1032, + 578, + 4198, + 22118, + 971, + 517, + 41953, + 933, + 368, + 45768, + 719, + 1030, + 368, + 319, + 7108, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.06937986261704389, + "compression_ratio": 1.6787003610108304, + "no_speech_prob": 5.948771558905719e-06, + "confidence": 0.972, + "words": [ + { + "text": "Et", + "start": 88.02, + "end": 88.48, + "confidence": 0.992 + }, + { + "text": "ce", + "start": 88.48, + "end": 88.86, + "confidence": 0.975 + }, + { + "text": "rapport,", + "start": 88.86, + "end": 89.28, + "confidence": 0.998 + }, + { + "text": "si", + "start": 89.28, + "end": 89.56, + "confidence": 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"confidence": 0.999 + }, + { + "text": "rejet.", + "start": 94.68, + "end": 95.14, + "confidence": 0.993 + } + ] + }, + { + "id": 19, + "seek": 7684, + "start": 95.78, + "end": 102.86, + "text": " Bon, en vrai, il faudrait remonter très très finement toute l'histoire des objets techniques et de leur insertion dans nos vies", + "tokens": [ + 7368, + 11, + 465, + 17815, + 11, + 1930, + 38694, + 8645, + 890, + 41806, + 5732, + 5732, + 962, + 1712, + 14953, + 287, + 6, + 29093, + 730, + 1111, + 25349, + 7512, + 1030, + 368, + 9580, + 8969, + 313, + 2680, + 3269, + 371, + 530 + ], + "temperature": 0.0, + "avg_logprob": -0.06937986261704389, + "compression_ratio": 1.6787003610108304, + "no_speech_prob": 5.948771558905719e-06, + "confidence": 0.941, + "words": [ + { + "text": "Bon,", + "start": 95.78, + "end": 96.38, + "confidence": 0.792 + }, + { + "text": "en", + "start": 96.38, + "end": 96.52, + "confidence": 0.998 + }, + { + "text": "vrai,", + "start": 96.52, + "end": 97.14, + 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Donc le rejet non plus n'était pas du même ordre.", + "tokens": [ + 6313, + 635, + 45768, + 719, + 297, + 6, + 9743, + 1736, + 1581, + 5698, + 4792, + 265, + 13, + 7477, + 476, + 319, + 7108, + 2107, + 1804, + 297, + 6, + 9743, + 1736, + 1581, + 5698, + 4792, + 265, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.07386374800172571, + "compression_ratio": 1.685512367491166, + "no_speech_prob": 5.46344235772267e-05, + "confidence": 0.972, + "words": [ + { + "text": "Mais", + "start": 115.34, + "end": 115.72, + "confidence": 0.994 + }, + { + "text": "la", + "start": 115.72, + "end": 116.02, + "confidence": 0.937 + }, + { + "text": "dépendance", + "start": 116.02, + "end": 116.4, + "confidence": 0.997 + }, + { + "text": "n'était", + "start": 116.4, + "end": 116.62, + "confidence": 0.994 + }, + { + "text": "pas", + "start": 116.62, + "end": 117.0, + "confidence": 0.998 + }, + { + "text": "du", + "start": 117.0, + "end": 117.16, + "confidence": 0.995 + }, + { + "text": "même", + "start": 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"id": 24, + "seek": 10584, + "start": 119.98, + "end": 123.02, + "text": " On peut adorer sa bagnole, en avoir besoin pour plein de choses.", + "tokens": [ + 1282, + 5977, + 614, + 17618, + 601, + 3411, + 1771, + 306, + 11, + 465, + 10853, + 19207, + 2016, + 21088, + 368, + 14488, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.07386374800172571, + "compression_ratio": 1.685512367491166, + "no_speech_prob": 5.46344235772267e-05, + "confidence": 0.991, + "words": [ + { + "text": "On", + "start": 119.98, + "end": 120.18, + "confidence": 0.996 + }, + { + "text": "peut", + "start": 120.18, + "end": 120.38, + "confidence": 0.997 + }, + { + "text": "adorer", + "start": 120.38, + "end": 120.66, + "confidence": 0.99 + }, + { + "text": "sa", + "start": 120.66, + "end": 120.88, + "confidence": 0.985 + }, + { + "text": "bagnole,", + "start": 120.88, + "end": 121.46, + "confidence": 0.984 + }, + { + "text": "en", + "start": 121.46, + "end": 121.56, + "confidence": 0.989 + }, + { + "text": 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26, + "seek": 10584, + "start": 126.98, + "end": 130.48, + "text": " On ne l'a pas dans la main quand on est au lit, on ne l'emmène pas au chiottes.", + "tokens": [ + 1282, + 408, + 287, + 6, + 64, + 1736, + 2680, + 635, + 2135, + 6932, + 322, + 871, + 1609, + 7997, + 11, + 322, + 408, + 287, + 6, + 443, + 76, + 18832, + 1736, + 1609, + 13228, + 1521, + 279, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.07386374800172571, + "compression_ratio": 1.685512367491166, + "no_speech_prob": 5.46344235772267e-05, + "confidence": 0.914, + "words": [ + { + "text": "On", + "start": 126.98, + "end": 127.32, + "confidence": 0.954 + }, + { + "text": "ne", + "start": 127.32, + "end": 127.36, + "confidence": 0.803 + }, + { + "text": "l'a", + "start": 127.36, + "end": 127.48, + "confidence": 0.974 + }, + { + "text": "pas", + "start": 127.48, + "end": 127.68, + "confidence": 0.999 + }, + { + "text": "dans", + "start": 127.68, + "end": 127.8, + "confidence": 0.996 + }, + { + "text": "la", + "start": 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D'accord. Mais pourquoi a-t-on l'impression qu'on n'en sortira jamais?", + "tokens": [ + 7477, + 11, + 18018, + 294, + 7811, + 270, + 13, + 413, + 6, + 19947, + 13, + 6313, + 19934, + 257, + 12, + 83, + 12, + 266, + 287, + 6, + 36107, + 421, + 6, + 266, + 297, + 6, + 268, + 1333, + 4271, + 14540, + 2506 + ], + "temperature": 0.0, + "avg_logprob": -0.06199159333200166, + "compression_ratio": 1.6127167630057804, + "no_speech_prob": 1.6126719856401905e-05, + "confidence": 0.948, + "words": [ + { + "text": "Donc,", + "start": 152.34, + "end": 153.46, + "confidence": 0.991 + }, + { + "text": "rapport", + "start": 153.46, + "end": 153.66, + "confidence": 0.976 + }, + { + "text": "inédit.", + "start": 153.66, + "end": 154.24, + "confidence": 0.996 + }, + { + "text": "D'accord.", + "start": 154.24, + "end": 155.48, + "confidence": 0.978 + }, + { + "text": "Mais", + "start": 155.48, + "end": 155.82, + "confidence": 0.557 + }, + { + "text": "pourquoi", + "start": 155.82, + "end": 156.32, + "confidence": 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ce que dit Nicolas, mais je ne me l'étais jamais formulé comme ça. Ce qui fait la force du smartphone, c'est pas seulement l'accumulation des fonctions, mais la manière dont elles interagissent entre elles. Ce qui dit d'ailleurs sur la photo, c'est hyper convaincant. Alors évidemment, il faudrait ajouter les interfaces. L'écran tactile a été beaucoup très souvent mentionné. Mais bon, il faut dire qu'il profite aussi de 20 ans pendant lesquels les ordinateurs nous ont appris à cliquer sur des icônes. Sauf que le smartphone ajoute le toucher, ce qui rend le contact plus direct, plus sensible. Et puis évidemment, il faudrait parler aussi des applications qui permettent de contourner le côté touffu de la navigation web pour aller directement au but. Bref, tout ça, ce sont les conditions qui permettent de créer cet objet dont Nicolas dit qu'il est vraisemblablement inédit dans l'histoire de l'humanité. Mais ça, ça soulève une autre interrogation. Est-ce que le fait que cet objet soit inédit induit que notre rapport à lui est aussi un rapport inédit ? Je veux dire, est-ce que le rapport qu'on a au smartphone est comparable à celui qu'on entretenait à d'autres objets techniques comme la voiture ou le téléphone ? Il n'y a pas d'équivalent en fait. Et donc cette espèce de nouveauté dans la relation à l'objet, c'est fascinant et terrifiant. Parce qu'on a l'impression, comme le disent les utilisateurs et les services, d'être dépendant de cet objet, d'induire en fait une espèce de relation, de médiation avec le monde qui rend de l'ampleur et qui amène aussi à des formes de rejet. Donc à objet inédit, rapport inédit. Et ce rapport, si j'en crois à Nicolas, serait caractérisé par un mélange de dépendance et de rejet. Bon, en vrai, il faudrait remonter très très finement toute l'histoire des objets techniques et de leur insertion dans nos vies pour déterminer si ce rapport est totalement inédit. Mais j'ai l'impression comme ça que Nicolas ne se trompe pas vraiment. Pour autant que je sache, il y a eu plein de discussions autour de la voiture ou même du téléphone. Mais la dépendance n'était pas du même ordre. Donc le rejet non plus n'était pas du même ordre. On peut adorer sa bagnole, en avoir besoin pour plein de choses. Le soir, quand on va se coucher, on la laisse. On ne l'a pas dans la main quand on est au lit, on ne l'emmène pas au chiottes. On pouvait être énervé par son môme qui occupait la ligne de téléphone pendant une heure chaque soir pour discuter avec un copain. Mais ça ne ressemblait pas à ce qu'on peut ressentir à voir ce même môme aujourd'hui, continuellement avec son smartphone dans la main, comme si c'était une sorte de pacemaker externe, comme si le lâcher allait entraîner sa mort immédiate. Bon, je dis ça pour le môme, mais c'est évidemment valable pour nous aussi. Donc, rapport inédit, d'accord. Mais pourquoi a-t-on l'impression qu'on n'en sortira jamais ? Est-ce qu'il faut en remettre la faute sur les gens qui ont créé cet outil merveilleux et diabolique, et diabolique parce que merveilleux ? Les économistes parlent de dépendance du sentier. C'est l'idée qu'on met sur un sentier qui a été établi, soit volontairement en marchant dessus, soit en définissant des bornes, en définissant une signalétique.", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.4, + "end": 3.66, + "text": " C'est évident ce que dit Nicolas, mais je ne me l'étais jamais formulé comme ça.", + "tokens": [ + 50364, + 383, + 6, + 377, + 20090, + 1078, + 1769, + 631, + 6176, + 38268, + 11, + 2420, + 1506, + 408, + 385, + 287, + 6, + 22824, + 14540, + 49990, + 526, + 5173, + 2788, + 13, + 50539 + ], + "temperature": 0.0, + "avg_logprob": -0.23621009675082782, + "compression_ratio": 1.6238532110091743, + "no_speech_prob": 0.1557241678237915, + "confidence": 0.935, + "words": [ + { + "text": "C'est", + "start": 0.4, + "end": 0.64, + "confidence": 0.961 + }, + { + "text": "évident", + "start": 0.64, + "end": 0.9, + "confidence": 0.984 + }, + { + "text": "ce", + "start": 0.9, + "end": 1.0, + "confidence": 0.663 + }, + { + "text": "que", + "start": 1.0, + 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"end": 82.62, + "confidence": 0.959 + }, + { + "text": "des", + "start": 82.62, + "end": 82.7, + "confidence": 0.992 + }, + { + "text": "formes", + "start": 82.7, + "end": 82.88, + "confidence": 0.995 + }, + { + "text": "de", + "start": 82.88, + "end": 83.04, + "confidence": 0.998 + }, + { + "text": "rejet.", + "start": 83.04, + "end": 83.3, + "confidence": 0.802 + } + ] + }, + { + "id": 17, + "seek": 7134, + "start": 83.92, + "end": 87.7, + "text": " Donc à objet inédit, rapport inédit.", + "tokens": [ + 50989, + 7477, + 1531, + 14964, + 294, + 7811, + 270, + 11, + 18018, + 294, + 7811, + 270, + 13, + 51189 + ], + "temperature": 0.0, + "avg_logprob": -0.11261525396573341, + "compression_ratio": 1.5975609756097562, + "no_speech_prob": 0.015181636437773705, + "confidence": 0.901, + "words": [ + { + "text": "Donc", + "start": 83.92, + "end": 84.46, + "confidence": 0.984 + }, + { + "text": "à", + "start": 84.46, + "end": 84.98, + "confidence": 0.481 + }, + { + "text": "objet", + "start": 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déterminer si ce rapport est totalement inédit.", + "tokens": [ + 50739, + 2016, + 2795, + 29725, + 260, + 1511, + 1769, + 18018, + 871, + 45203, + 294, + 7811, + 270, + 13, + 50889 + ], + "temperature": 0.0, + "avg_logprob": -0.07804971811722736, + "compression_ratio": 1.6719745222929936, + "no_speech_prob": 0.017434893175959587, + "confidence": 0.995, + "words": [ + { + "text": "pour", + "start": 102.86, + "end": 103.1, + "confidence": 0.989 + }, + { + "text": "déterminer", + "start": 103.1, + "end": 103.64, + "confidence": 0.995 + }, + { + "text": "si", + "start": 103.64, + "end": 103.76, + "confidence": 0.986 + }, + { + "text": "ce", + "start": 103.76, + "end": 103.94, + "confidence": 0.991 + }, + { + "text": "rapport", + "start": 103.94, + "end": 104.26, + "confidence": 0.998 + }, + { + "text": "est", + "start": 104.26, + "end": 104.84, + "confidence": 0.997 + }, + { + "text": "totalement", + "start": 104.84, + "end": 105.3, + "confidence": 0.998 + }, + { + "text": "inédit.", + 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pas du même ordre.", + "tokens": [ + 51389, + 6313, + 635, + 45768, + 719, + 297, + 6, + 9743, + 1736, + 1581, + 5698, + 4792, + 265, + 13, + 51489 + ], + "temperature": 0.0, + "avg_logprob": -0.07804971811722736, + "compression_ratio": 1.6719745222929936, + "no_speech_prob": 0.017434893175959587, + "confidence": 0.992, + "words": [ + { + "text": "Mais", + "start": 115.48, + "end": 115.78, + "confidence": 0.993 + }, + { + "text": "la", + "start": 115.78, + "end": 116.04, + "confidence": 0.944 + }, + { + "text": "dépendance", + "start": 116.04, + "end": 116.42, + "confidence": 0.996 + }, + { + "text": "n'était", + "start": 116.42, + "end": 116.7, + "confidence": 0.994 + }, + { + "text": "pas", + "start": 116.7, + "end": 117.0, + "confidence": 0.998 + }, + { + "text": "du", + "start": 117.0, + "end": 117.2, + "confidence": 0.996 + }, + { + "text": "même", + "start": 117.2, + "end": 117.44, + "confidence": 0.998 + }, + { + "text": "ordre.", + "start": 117.44, + "end": 117.7, + 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" Mais ça ne ressemblait pas à ce qu'on peut ressentir à voir ce même môme aujourd'hui,", + "tokens": [ + 51039, + 6313, + 2788, + 408, + 725, + 15750, + 35235, + 1736, + 1531, + 1769, + 421, + 6, + 266, + 5977, + 24689, + 317, + 347, + 1531, + 10695, + 1769, + 5698, + 275, + 2851, + 1398, + 14023, + 6, + 10556, + 11, + 51289 + ], + "temperature": 0.0, + "avg_logprob": -0.08259125505940298, + "compression_ratio": 1.6818181818181819, + "no_speech_prob": 0.011154274456202984, + "confidence": 0.956, + "words": [ + { + "text": "Mais", + "start": 137.26, + "end": 137.5, + "confidence": 0.989 + }, + { + "text": "ça", + "start": 137.5, + "end": 137.68, + "confidence": 0.927 + }, + { + "text": "ne", + "start": 137.68, + "end": 137.88, + "confidence": 0.999 + }, + { + "text": "ressemblait", + "start": 137.88, + "end": 138.42, + "confidence": 0.993 + }, + { + "text": "pas", + "start": 138.42, + "end": 138.78, + "confidence": 0.995 + }, + { + "text": "à", + "start": 138.78, + "end": 138.9, + 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smartphone dans la main,", + "tokens": [ + 51289, + 2354, + 285, + 1712, + 4163, + 1872, + 13307, + 2680, + 635, + 2135, + 11, + 51414 + ], + "temperature": 0.0, + "avg_logprob": -0.08259125505940298, + "compression_ratio": 1.6818181818181819, + "no_speech_prob": 0.011154274456202984, + "confidence": 0.961, + "words": [ + { + "text": "continuellement", + "start": 142.16, + "end": 142.94, + "confidence": 0.963 + }, + { + "text": "avec", + "start": 142.94, + "end": 143.2, + "confidence": 0.844 + }, + { + "text": "son", + "start": 143.2, + "end": 143.42, + "confidence": 0.994 + }, + { + "text": "smartphone", + "start": 143.42, + "end": 143.76, + "confidence": 0.972 + }, + { + "text": "dans", + "start": 143.76, + "end": 143.92, + "confidence": 0.964 + }, + { + "text": "la", + "start": 143.92, + "end": 144.02, + "confidence": 0.997 + }, + { + "text": "main,", + "start": 144.02, + "end": 144.22, + "confidence": 0.997 + } + ] + }, + { + "id": 31, + "seek": 12334, + "start": 144.34, + "end": 148.8, + "text": " comme si c'était une sorte de pacemaker externe, comme si le lâcher allait entraîner sa mort immédiate.", + "tokens": [ + 51414, + 5173, + 1511, + 269, + 6, + 9743, + 2251, + 25559, + 368, + 15165, + 49523, + 454, + 391, + 716, + 11, + 5173, + 1511, + 476, + 48835, + 6759, + 439, + 1001, + 22284, + 7517, + 1193, + 601, + 6599, + 3397, + 526, + 4504, + 473, + 13, + 51639 + ], + "temperature": 0.0, + "avg_logprob": -0.08259125505940298, + "compression_ratio": 1.6818181818181819, + "no_speech_prob": 0.011154274456202984, + "confidence": 0.973, + "words": [ + { + "text": "comme", + "start": 144.34, + "end": 144.56, + "confidence": 0.985 + }, + { + "text": "si", + "start": 144.56, + "end": 144.66, + "confidence": 0.972 + }, + { + "text": "c'était", + "start": 144.66, + "end": 144.86, + "confidence": 0.987 + }, + { + "text": "une", + "start": 144.86, + "end": 144.98, + "confidence": 0.983 + }, + { + "text": "sorte", + "start": 144.98, + "end": 145.14, + "confidence": 0.992 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your Soyuz-EA GLEM-E-G-E-A. All right. Okay. Yeah, sir. Yeah, sir. Let's take that camera. Let's say it makes it want to go on the helmet we were going to have in B-1. The other one. And you can put the other one on the mic helmet. We'll show it to you in a quick screen. Over. All right. Yeah, sir. All right. Yeah, sir. There's a better helmet than B-1. That's the other one. Nice. Let's go in there. At least we're safe. We've got them in there. Helmet bags. And, uh, I guess we have helmets in the helmet bag. At least it's in the helmet bag. Right here. Right here. Yeah, we're taking it next day out of the field up. Hey, we were... You want to hack me on this? Hey, we were... You want to hack me on this? With a cover, I tried it already. Okay, fine. We weren't sure of that. Just a suggestion. We thought we'd... You could check it out. It's not much of an order to turn that. So, uh, I guess we're going to come up with this. Let us know. Okay. No problem. Okay. No problem. We'll let you know when the end of... None. 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Alright, okay, we like to say that they make the one that's on the helmet we're going to have in B1. And you can put the other one on the mic helmet with those GVA blizzard frames. 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All right. Okay. Yeah, sir. Yeah, sir. Let's take that camera. Let's say it makes it want to go on the helmet we were going to have in B-1. The other one. And you can put the other one on the mic helmet. We'll show it to you in a quick screen. Over. All right. Yeah, sir. All right. Yeah, sir. There's a better helmet than B-1. That's the other one. Nice. Let's go in there. At least we're safe. We've got them in there. Helmet bags. And, uh, I guess we have helmets in the helmet bag. At least it's in the helmet bag. Right here. Right here. Yeah, we're taking it next day out of the field up. Yeah, we were. You want to hack me on that? Yeah, we were. You want to hack me on that? With the cover, I tried it already. Okay, fine. We weren't sure of that. Just a suggestion. We thought we'd, uh, say you could check it out. It's not much of an order to turn that. So, uh, I guess we're going to come up with this. Let us know. Okay. No problem. Okay. No problem. No problem. No problem. No problem. No problem. No problem. 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Alright, okay, we like to say that they make the one that's on the helmet we're going to have in B1. And you can put the other one on the mic helmet with those GVA blizzard frames. Alright, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, 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All right. Okay. Yeah, sir. Yeah, sir. Let's take that camera. Let's say it makes it want to go on the helmet we were going to have in B-1. The other one. And you can put the other one on the mic helmet. We'll show it to you in a quick screen. Over. All right. Yeah, sir. All right. Yeah, sir. There's a better helmet than B-1. That's the other one. Nice. Let's go in there. At least we're safe. We've got them in there. Helmet bags. And, uh, I guess we have helmets in the helmet bag. At least it's in the helmet bag. Right here. Right here. Yeah, we're taking it next day. Yeah, we're taking it next day. Yeah, it's a little bit of a delay on it. Yeah, you know what. We're gonna hack me on it. We're gonna hack you on it. We're gonna hack you on it. We're gonna hack you on it. With a cover, I tried it already. Okay, fine. We weren't sure of that, uh, just the suggestion. We thought we'd, uh, say you could check it out. It's not much of a hard to turn on, so, uh, I guess, uh, we're gonna come up with it. Let us know. Okay, no problem. Okay, no problem. We're gonna let you know when the end of... None. I'm glad you came. Everything's OK. Everything's OK. Yeah. 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Apollo 11, Houston we got a recommendation for you on your Soyuz-VA GLEME GVA. Alright, okay, we like to say that they make the one that's on the helmet we're going to have in B1. And you can put the other one on the mic helmet with those GVA blizzard frames. Alright, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, got them, 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b/tests/expected/punctuations_no/bonjour.wav.srt new file mode 100644 index 0000000000000000000000000000000000000000..d8d205dc3daf944fcf8cbd38edc5f45287fb5510 --- /dev/null +++ b/tests/expected/punctuations_no/bonjour.wav.srt @@ -0,0 +1,4 @@ +1 +00:00:00,140 --> 00:00:00,940 +Bonjour ! + diff --git a/tests/expected/punctuations_no/bonjour.wav.tsv b/tests/expected/punctuations_no/bonjour.wav.tsv new file mode 100644 index 0000000000000000000000000000000000000000..4244f49ea0e650559f762b334550dd60e0a2f2a6 --- /dev/null +++ b/tests/expected/punctuations_no/bonjour.wav.tsv @@ -0,0 +1,2 @@ +start end text +140 940 Bonjour ! diff --git a/tests/expected/punctuations_no/bonjour.wav.txt b/tests/expected/punctuations_no/bonjour.wav.txt new file mode 100644 index 0000000000000000000000000000000000000000..6625d5f9893711f1c711cc5a3695219d1f4d9cc4 --- /dev/null +++ b/tests/expected/punctuations_no/bonjour.wav.txt @@ -0,0 +1 @@ +Bonjour ! diff --git a/tests/expected/punctuations_no/bonjour.wav.vtt b/tests/expected/punctuations_no/bonjour.wav.vtt new file mode 100644 index 0000000000000000000000000000000000000000..ecc03120fcb44b8ed669288169bdae00ce0c79ec --- /dev/null +++ b/tests/expected/punctuations_no/bonjour.wav.vtt @@ -0,0 +1,7 @@ +WEBVTT + +WEBVTT + +00:00.140 --> 00:00.940 +Bonjour ! + diff --git a/tests/expected/punctuations_no/bonjour.wav.words.csv b/tests/expected/punctuations_no/bonjour.wav.words.csv new file mode 100644 index 0000000000000000000000000000000000000000..2ebbe298c64c70895fa7d45404203bc3a58d99d0 --- /dev/null +++ b/tests/expected/punctuations_no/bonjour.wav.words.csv @@ -0,0 +1 @@ +Bonjour,0.14,0.94 diff --git a/tests/expected/punctuations_no/bonjour.wav.words.json b/tests/expected/punctuations_no/bonjour.wav.words.json new file mode 100644 index 0000000000000000000000000000000000000000..be46e53f9a139741c8adee254f302e95fada75b9 --- /dev/null +++ b/tests/expected/punctuations_no/bonjour.wav.words.json @@ -0,0 +1,32 @@ +{ + "text": " Bonjour !", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.14, + "end": 0.94, + "text": " Bonjour !", + "tokens": [ + 50364, + 25431, + 2298, + 50402 + ], + "temperature": 0.0, + "avg_logprob": -0.7047327041625977, + "compression_ratio": 0.5294117647058824, + "no_speech_prob": 0.08847080171108246, + "confidence": 0.964, + "words": [ + { + "text": "Bonjour", + "start": 0.14, + "end": 0.94, + "confidence": 0.964 + } + ] + } + ], + "language": "fr" +} \ No newline at end of file diff --git a/tests/expected/punctuations_no/bonjour.wav.words.srt b/tests/expected/punctuations_no/bonjour.wav.words.srt new file mode 100644 index 0000000000000000000000000000000000000000..cd14abb1f5b082f428f7e68574088414fa661db8 --- /dev/null +++ b/tests/expected/punctuations_no/bonjour.wav.words.srt @@ -0,0 +1,4 @@ +1 +00:00:00,140 --> 00:00:00,940 +Bonjour + diff --git a/tests/expected/punctuations_no/bonjour.wav.words.tsv b/tests/expected/punctuations_no/bonjour.wav.words.tsv new file mode 100644 index 0000000000000000000000000000000000000000..2ddd00966ddffa056b18e3903294c7ef5795ffe1 --- /dev/null +++ b/tests/expected/punctuations_no/bonjour.wav.words.tsv @@ -0,0 +1,2 @@ +start end text +140 940 Bonjour diff --git a/tests/expected/punctuations_no/bonjour.wav.words.vtt b/tests/expected/punctuations_no/bonjour.wav.words.vtt new file mode 100644 index 0000000000000000000000000000000000000000..a3ce34860a05ec1125085a02e60a5eac85458c72 --- /dev/null +++ b/tests/expected/punctuations_no/bonjour.wav.words.vtt @@ -0,0 +1,7 @@ +WEBVTT + +WEBVTT + +00:00.140 --> 00:00.940 +Bonjour + diff --git a/tests/expected/punctuations_no/punctuations.mp3.csv b/tests/expected/punctuations_no/punctuations.mp3.csv new file mode 100644 index 0000000000000000000000000000000000000000..99139dd1ffcb8551acde7072c34682a561976ead --- /dev/null +++ b/tests/expected/punctuations_no/punctuations.mp3.csv @@ -0,0 +1 @@ +"Dis-moi, est-ce que l'avion vole ?",0.38,2.76 diff --git a/tests/expected/punctuations_no/punctuations.mp3.srt b/tests/expected/punctuations_no/punctuations.mp3.srt new file mode 100644 index 0000000000000000000000000000000000000000..877851ff9664283f0877d16b24551fa2d7a88226 --- /dev/null +++ b/tests/expected/punctuations_no/punctuations.mp3.srt @@ -0,0 +1,4 @@ +1 +00:00:00,380 --> 00:00:02,760 +Dis-moi, est-ce que l'avion vole ? + diff --git a/tests/expected/punctuations_no/punctuations.mp3.tsv b/tests/expected/punctuations_no/punctuations.mp3.tsv new file mode 100644 index 0000000000000000000000000000000000000000..58cf737627008302c822b962a66b0b7e46a3a1de --- /dev/null +++ b/tests/expected/punctuations_no/punctuations.mp3.tsv @@ -0,0 +1,2 @@ +start end text +380 2760 Dis-moi, est-ce que l'avion vole ? diff --git a/tests/expected/punctuations_no/punctuations.mp3.txt b/tests/expected/punctuations_no/punctuations.mp3.txt new file mode 100644 index 0000000000000000000000000000000000000000..6490b685ff0adf8d95873de48095732fd91c30fd --- /dev/null +++ b/tests/expected/punctuations_no/punctuations.mp3.txt @@ -0,0 +1 @@ +Dis-moi, est-ce que l'avion vole ? diff --git a/tests/expected/punctuations_no/punctuations.mp3.vtt b/tests/expected/punctuations_no/punctuations.mp3.vtt new file mode 100644 index 0000000000000000000000000000000000000000..8397a28e233bce3dbd3ddbf7a4226bf3c210e870 --- /dev/null +++ b/tests/expected/punctuations_no/punctuations.mp3.vtt @@ -0,0 +1,7 @@ +WEBVTT + +WEBVTT + +00:00.380 --> 00:02.760 +Dis-moi, est-ce que l'avion vole ? + diff --git a/tests/expected/punctuations_no/punctuations.mp3.words.csv b/tests/expected/punctuations_no/punctuations.mp3.words.csv new file mode 100644 index 0000000000000000000000000000000000000000..69362f890ad8d996e811cebb54bfabcdd64daf63 --- /dev/null +++ b/tests/expected/punctuations_no/punctuations.mp3.words.csv @@ -0,0 +1,5 @@ +Dis-moi,0.38,1.1 +est-ce,1.28,1.5 +que,1.5,1.66 +l'avion,1.66,2.04 +vole,2.04,2.76 diff --git a/tests/expected/punctuations_no/punctuations.mp3.words.json b/tests/expected/punctuations_no/punctuations.mp3.words.json new file mode 100644 index 0000000000000000000000000000000000000000..3dc1f87e063dbd458cc97bf2e6ed781d223ac7da --- /dev/null +++ b/tests/expected/punctuations_no/punctuations.mp3.words.json @@ -0,0 +1,68 @@ +{ + "text": " Dis-moi, est-ce que l'avion vole ?", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.38, + "end": 2.76, + "text": " Dis-moi, est-ce que l'avion vole ?", + "tokens": [ + 50364, + 4208, + 12, + 29292, + 11, + 871, + 12, + 384, + 631, + 287, + 6, + 706, + 313, + 49877, + 2506, + 50496 + ], + "temperature": 0.0, + "avg_logprob": -0.26349667941822724, + "compression_ratio": 0.8095238095238095, + "no_speech_prob": 0.03940592333674431, + "confidence": 0.928, + "words": [ + { + "text": "Dis-moi", + "start": 0.38, + "end": 1.1, + "confidence": 0.807 + }, + { + "text": "est-ce", + "start": 1.28, + "end": 1.5, + "confidence": 0.968 + }, + { + "text": "que", + "start": 1.5, + "end": 1.66, + "confidence": 0.978 + }, + { + "text": "l'avion", + "start": 1.66, + "end": 2.04, + "confidence": 0.993 + }, + { + "text": "vole", + "start": 2.04, + "end": 2.76, + "confidence": 0.898 + } + ] + } + ], + "language": "fr" +} \ No newline at end of file diff --git a/tests/expected/punctuations_no/punctuations.mp3.words.srt b/tests/expected/punctuations_no/punctuations.mp3.words.srt new file mode 100644 index 0000000000000000000000000000000000000000..9a0041e682bad02b37134d8a0d764cd07b64f608 --- /dev/null +++ b/tests/expected/punctuations_no/punctuations.mp3.words.srt @@ -0,0 +1,20 @@ +1 +00:00:00,380 --> 00:00:01,100 +Dis-moi + +2 +00:00:01,280 --> 00:00:01,500 +est-ce + +3 +00:00:01,500 --> 00:00:01,660 +que + +4 +00:00:01,660 --> 00:00:02,040 +l'avion + +5 +00:00:02,040 --> 00:00:02,760 +vole + diff --git a/tests/expected/punctuations_no/punctuations.mp3.words.tsv b/tests/expected/punctuations_no/punctuations.mp3.words.tsv new file mode 100644 index 0000000000000000000000000000000000000000..a9613c4fe6697b2aa5ea56eecd09fb9c18d32210 --- /dev/null +++ b/tests/expected/punctuations_no/punctuations.mp3.words.tsv @@ -0,0 +1,6 @@ +start end text +380 1100 Dis-moi +1280 1500 est-ce +1500 1660 que +1660 2040 l'avion +2040 2760 vole diff --git a/tests/expected/punctuations_no/punctuations.mp3.words.vtt b/tests/expected/punctuations_no/punctuations.mp3.words.vtt new file mode 100644 index 0000000000000000000000000000000000000000..fc6f8a3b6558650512d59fcdc3ce41735b03176d --- /dev/null +++ b/tests/expected/punctuations_no/punctuations.mp3.words.vtt @@ -0,0 +1,19 @@ +WEBVTT + +WEBVTT + +00:00.380 --> 00:01.100 +Dis-moi + +00:01.280 --> 00:01.500 +est-ce + +00:01.500 --> 00:01.660 +que + +00:01.660 --> 00:02.040 +l'avion + +00:02.040 --> 00:02.760 +vole + diff --git a/tests/expected/punctuations_yes/bonjour.wav.csv b/tests/expected/punctuations_yes/bonjour.wav.csv new file mode 100644 index 0000000000000000000000000000000000000000..5cbf6b2289864210ec6373166aa3e624eba1bde6 --- /dev/null +++ b/tests/expected/punctuations_yes/bonjour.wav.csv @@ -0,0 +1 @@ +Bonjour !,0.14,0.94 diff --git a/tests/expected/punctuations_yes/bonjour.wav.srt b/tests/expected/punctuations_yes/bonjour.wav.srt new file mode 100644 index 0000000000000000000000000000000000000000..d8d205dc3daf944fcf8cbd38edc5f45287fb5510 --- /dev/null +++ b/tests/expected/punctuations_yes/bonjour.wav.srt @@ -0,0 +1,4 @@ +1 +00:00:00,140 --> 00:00:00,940 +Bonjour ! + diff --git a/tests/expected/punctuations_yes/bonjour.wav.tsv b/tests/expected/punctuations_yes/bonjour.wav.tsv new file mode 100644 index 0000000000000000000000000000000000000000..4244f49ea0e650559f762b334550dd60e0a2f2a6 --- /dev/null +++ b/tests/expected/punctuations_yes/bonjour.wav.tsv @@ -0,0 +1,2 @@ +start end text +140 940 Bonjour ! diff --git a/tests/expected/punctuations_yes/bonjour.wav.txt b/tests/expected/punctuations_yes/bonjour.wav.txt new file mode 100644 index 0000000000000000000000000000000000000000..6625d5f9893711f1c711cc5a3695219d1f4d9cc4 --- /dev/null +++ b/tests/expected/punctuations_yes/bonjour.wav.txt @@ -0,0 +1 @@ +Bonjour ! diff --git a/tests/expected/punctuations_yes/bonjour.wav.vtt b/tests/expected/punctuations_yes/bonjour.wav.vtt new file mode 100644 index 0000000000000000000000000000000000000000..ecc03120fcb44b8ed669288169bdae00ce0c79ec --- /dev/null +++ b/tests/expected/punctuations_yes/bonjour.wav.vtt @@ -0,0 +1,7 @@ +WEBVTT + +WEBVTT + +00:00.140 --> 00:00.940 +Bonjour ! + diff --git a/tests/expected/punctuations_yes/bonjour.wav.words.csv b/tests/expected/punctuations_yes/bonjour.wav.words.csv new file mode 100644 index 0000000000000000000000000000000000000000..5cbf6b2289864210ec6373166aa3e624eba1bde6 --- /dev/null +++ b/tests/expected/punctuations_yes/bonjour.wav.words.csv @@ -0,0 +1 @@ +Bonjour !,0.14,0.94 diff --git a/tests/expected/punctuations_yes/bonjour.wav.words.json b/tests/expected/punctuations_yes/bonjour.wav.words.json new file mode 100644 index 0000000000000000000000000000000000000000..0ceff460cfed744a26ce7dd494b00fb39619a892 --- /dev/null +++ b/tests/expected/punctuations_yes/bonjour.wav.words.json @@ -0,0 +1,32 @@ +{ + "text": " Bonjour !", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.14, + "end": 0.94, + "text": " Bonjour !", + "tokens": [ + 50364, + 25431, + 2298, + 50402 + ], + "temperature": 0.0, + "avg_logprob": -0.7047327041625977, + "compression_ratio": 0.5294117647058824, + "no_speech_prob": 0.08847080171108246, + "confidence": 0.964, + "words": [ + { + "text": "Bonjour !", + "start": 0.14, + "end": 0.94, + "confidence": 0.964 + } + ] + } + ], + "language": "fr" +} \ No newline at end of file diff --git a/tests/expected/punctuations_yes/bonjour.wav.words.srt b/tests/expected/punctuations_yes/bonjour.wav.words.srt new file mode 100644 index 0000000000000000000000000000000000000000..d8d205dc3daf944fcf8cbd38edc5f45287fb5510 --- /dev/null +++ b/tests/expected/punctuations_yes/bonjour.wav.words.srt @@ -0,0 +1,4 @@ +1 +00:00:00,140 --> 00:00:00,940 +Bonjour ! + diff --git a/tests/expected/punctuations_yes/bonjour.wav.words.tsv b/tests/expected/punctuations_yes/bonjour.wav.words.tsv new file mode 100644 index 0000000000000000000000000000000000000000..4244f49ea0e650559f762b334550dd60e0a2f2a6 --- /dev/null +++ b/tests/expected/punctuations_yes/bonjour.wav.words.tsv @@ -0,0 +1,2 @@ +start end text +140 940 Bonjour ! diff --git a/tests/expected/punctuations_yes/bonjour.wav.words.vtt b/tests/expected/punctuations_yes/bonjour.wav.words.vtt new file mode 100644 index 0000000000000000000000000000000000000000..ecc03120fcb44b8ed669288169bdae00ce0c79ec --- /dev/null +++ b/tests/expected/punctuations_yes/bonjour.wav.words.vtt @@ -0,0 +1,7 @@ +WEBVTT + +WEBVTT + +00:00.140 --> 00:00.940 +Bonjour ! + diff --git a/tests/expected/punctuations_yes/punctuations.mp3.csv b/tests/expected/punctuations_yes/punctuations.mp3.csv new file mode 100644 index 0000000000000000000000000000000000000000..99139dd1ffcb8551acde7072c34682a561976ead --- /dev/null +++ b/tests/expected/punctuations_yes/punctuations.mp3.csv @@ -0,0 +1 @@ +"Dis-moi, est-ce que l'avion vole ?",0.38,2.76 diff --git a/tests/expected/punctuations_yes/punctuations.mp3.srt b/tests/expected/punctuations_yes/punctuations.mp3.srt new file mode 100644 index 0000000000000000000000000000000000000000..877851ff9664283f0877d16b24551fa2d7a88226 --- /dev/null +++ b/tests/expected/punctuations_yes/punctuations.mp3.srt @@ -0,0 +1,4 @@ +1 +00:00:00,380 --> 00:00:02,760 +Dis-moi, est-ce que l'avion vole ? + diff --git a/tests/expected/punctuations_yes/punctuations.mp3.tsv b/tests/expected/punctuations_yes/punctuations.mp3.tsv new file mode 100644 index 0000000000000000000000000000000000000000..58cf737627008302c822b962a66b0b7e46a3a1de --- /dev/null +++ b/tests/expected/punctuations_yes/punctuations.mp3.tsv @@ -0,0 +1,2 @@ +start end text +380 2760 Dis-moi, est-ce que l'avion vole ? diff --git a/tests/expected/punctuations_yes/punctuations.mp3.txt b/tests/expected/punctuations_yes/punctuations.mp3.txt new file mode 100644 index 0000000000000000000000000000000000000000..6490b685ff0adf8d95873de48095732fd91c30fd --- /dev/null +++ b/tests/expected/punctuations_yes/punctuations.mp3.txt @@ -0,0 +1 @@ +Dis-moi, est-ce que l'avion vole ? diff --git a/tests/expected/punctuations_yes/punctuations.mp3.vtt b/tests/expected/punctuations_yes/punctuations.mp3.vtt new file mode 100644 index 0000000000000000000000000000000000000000..8397a28e233bce3dbd3ddbf7a4226bf3c210e870 --- /dev/null +++ b/tests/expected/punctuations_yes/punctuations.mp3.vtt @@ -0,0 +1,7 @@ +WEBVTT + +WEBVTT + +00:00.380 --> 00:02.760 +Dis-moi, est-ce que l'avion vole ? + diff --git a/tests/expected/punctuations_yes/punctuations.mp3.words.csv b/tests/expected/punctuations_yes/punctuations.mp3.words.csv new file mode 100644 index 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b/tests/expected/split_subtitles/punctuations.mp3_20.srt @@ -0,0 +1,12 @@ +1 +00:00:00,400 --> 00:00:01,360 +Dis-moi, + +2 +00:00:01,360 --> 00:00:02,020 +est-ce que l'avion + +3 +00:00:02,020 --> 00:00:02,340 +vole? + diff --git a/tests/expected/split_subtitles/punctuations.mp3_20.vtt b/tests/expected/split_subtitles/punctuations.mp3_20.vtt new file mode 100644 index 0000000000000000000000000000000000000000..d06e85098725e851017bd86f94fa529b5c66d030 --- /dev/null +++ b/tests/expected/split_subtitles/punctuations.mp3_20.vtt @@ -0,0 +1,11 @@ +WEBVTT + +00:00.400 --> 00:01.360 +Dis-moi, + +00:01.360 --> 00:02.020 +est-ce que l'avion + +00:02.020 --> 00:02.340 +vole? + diff --git a/tests/expected/split_subtitles/punctuations.mp3_50.srt b/tests/expected/split_subtitles/punctuations.mp3_50.srt new file mode 100644 index 0000000000000000000000000000000000000000..ffc9a2b42b2c510691ec27b303df2c88825c0aa4 --- /dev/null +++ b/tests/expected/split_subtitles/punctuations.mp3_50.srt @@ -0,0 +1,4 @@ +1 +00:00:00,400 --> 00:00:02,340 +Dis-moi, est-ce que l'avion vole? + diff --git a/tests/expected/split_subtitles/punctuations.mp3_50.vtt b/tests/expected/split_subtitles/punctuations.mp3_50.vtt new file mode 100644 index 0000000000000000000000000000000000000000..83c7bd9a0253ca6a8d117803fac3a2bdc3b9e525 --- /dev/null +++ b/tests/expected/split_subtitles/punctuations.mp3_50.vtt @@ -0,0 +1,5 @@ +WEBVTT + +00:00.400 --> 00:02.340 +Dis-moi, est-ce que l'avion vole? + diff --git a/tests/expected/split_subtitles/punctuations.mp3_6.srt b/tests/expected/split_subtitles/punctuations.mp3_6.srt new file mode 100644 index 0000000000000000000000000000000000000000..0caea3d7e82a647c78c154e2d1879292e5442c9d --- /dev/null +++ b/tests/expected/split_subtitles/punctuations.mp3_6.srt @@ -0,0 +1,20 @@ +1 +00:00:00,400 --> 00:00:01,360 +Dis-moi, + +2 +00:00:01,360 --> 00:00:01,520 +est-ce + +3 +00:00:01,520 --> 00:00:01,640 +que + +4 +00:00:01,640 --> 00:00:02,020 +l'avion + +5 +00:00:02,020 --> 00:00:02,340 +vole? + diff --git a/tests/expected/split_subtitles/punctuations.mp3_6.vtt b/tests/expected/split_subtitles/punctuations.mp3_6.vtt new file mode 100644 index 0000000000000000000000000000000000000000..f255e42075a222812432fc82fe6622c86de71015 --- /dev/null +++ b/tests/expected/split_subtitles/punctuations.mp3_6.vtt @@ -0,0 +1,17 @@ +WEBVTT + +00:00.400 --> 00:01.360 +Dis-moi, + +00:01.360 --> 00:01.520 +est-ce + +00:01.520 --> 00:01.640 +que + +00:01.640 --> 00:02.020 +l'avion + +00:02.020 --> 00:02.340 +vole? + diff --git a/tests/expected/split_subtitles/smartphone.mp3_20.srt b/tests/expected/split_subtitles/smartphone.mp3_20.srt new file mode 100644 index 0000000000000000000000000000000000000000..22c039440f6cb0beda8f9ccf043d766a717ac78a --- /dev/null +++ b/tests/expected/split_subtitles/smartphone.mp3_20.srt @@ -0,0 +1,812 @@ +1 +00:00:00,380 --> 00:00:01,080 +C'est évident ce que + +2 +00:00:01,080 --> 00:00:01,780 +dit Nicolas, + +3 +00:00:01,780 --> 00:00:02,380 +mais je ne me + +4 +00:00:02,380 --> 00:00:02,840 +l'étais jamais + +5 +00:00:02,840 --> 00:00:03,620 +formulé comme ça. + +6 +00:00:04,080 --> 00:00:05,000 +Ce qui fait la force + +7 +00:00:05,000 --> 00:00:05,880 +du smartphone, + +8 +00:00:05,880 --> 00:00:06,520 +c'est pas seulement + +9 +00:00:06,520 --> 00:00:07,560 +l'accumulation des + +10 +00:00:07,560 --> 00:00:07,920 +fonctions, + +11 +00:00:08,320 --> 00:00:09,100 +mais la manière dont + +12 +00:00:09,100 --> 00:00:10,320 +elles interagissent + +13 +00:00:10,320 --> 00:00:10,880 +entre elles. + +14 +00:00:10,960 --> 00:00:11,400 +Ce qui dit + +15 +00:00:11,400 --> 00:00:11,780 +d'ailleurs sur la + +16 +00:00:11,780 --> 00:00:12,120 +photo, + +17 +00:00:12,120 --> 00:00:13,000 +c'est hyper convaincant. + +18 +00:00:13,340 --> 00:00:14,340 +Alors évidemment, + +19 +00:00:14,340 --> 00:00:15,160 +il faudrait ajouter + +20 +00:00:15,160 --> 00:00:16,020 +les interfaces. + +21 +00:00:16,220 --> 00:00:17,260 +L'écran tactile a + +22 +00:00:17,260 --> 00:00:18,620 +été beaucoup très + +23 +00:00:18,620 --> 00:00:19,360 +souvent mentionné. + +24 +00:00:19,840 --> 00:00:20,520 +Mais bon, + +25 +00:00:20,520 --> 00:00:20,960 +il faut dire qu'il + +26 +00:00:20,960 --> 00:00:22,100 +profite aussi de 20 + +27 +00:00:22,100 --> 00:00:22,920 +ans pendant lesquels + +28 +00:00:22,920 --> 00:00:23,720 +les ordinateurs nous + +29 +00:00:23,720 --> 00:00:24,500 +ont appris à cliquer + +30 +00:00:24,500 --> 00:00:25,260 +sur des icônes. + +31 +00:00:25,420 --> 00:00:26,660 +Sauf que le + +32 +00:00:26,660 --> 00:00:27,620 +smartphone ajoute le + +33 +00:00:27,620 --> 00:00:28,180 +toucher, + +34 +00:00:28,180 --> 00:00:28,680 +ce qui rend le + +35 +00:00:28,680 --> 00:00:30,220 +contact plus direct, + +36 +00:00:30,220 --> 00:00:30,640 +plus sensible. + +37 +00:00:31,040 --> 00:00:31,700 +Et puis évidemment, + +38 +00:00:31,700 --> 00:00:32,120 +il faudrait parler + +39 +00:00:32,120 --> 00:00:32,480 +aussi des + +40 +00:00:32,480 --> 00:00:33,180 +applications qui + +41 +00:00:33,180 --> 00:00:33,960 +permettent de + +42 +00:00:33,960 --> 00:00:34,800 +contourner le côté + +43 +00:00:34,800 --> 00:00:35,780 +touffu de la + +44 +00:00:35,780 --> 00:00:36,780 +navigation web pour + +45 +00:00:36,780 --> 00:00:37,680 +aller directement au + +46 +00:00:37,680 --> 00:00:37,820 +but. + +47 +00:00:37,820 --> 00:00:39,420 +Bref, tout ça, + +48 +00:00:39,420 --> 00:00:40,160 +ce sont les + +49 +00:00:40,160 --> 00:00:40,960 +conditions qui + +50 +00:00:40,960 --> 00:00:42,060 +permettent de créer + +51 +00:00:42,060 --> 00:00:42,800 +cet objet dont + +52 +00:00:42,800 --> 00:00:43,700 +Nicolas dit qu'il + +53 +00:00:43,700 --> 00:00:43,880 +est + +54 +00:00:43,880 --> 00:00:44,980 +vraisemblablement + +55 +00:00:44,980 --> 00:00:45,700 +inédit dans + +56 +00:00:45,700 --> 00:00:46,180 +l'histoire de + +57 +00:00:46,180 --> 00:00:46,580 +l'humanité. + +58 +00:00:46,600 --> 00:00:47,720 +Mais ça, + +59 +00:00:47,720 --> 00:00:48,260 +ça soulève une autre + +60 +00:00:48,260 --> 00:00:48,820 +interrogation. + +61 +00:00:49,220 --> 00:00:49,980 +Est-ce que le fait + +62 +00:00:49,980 --> 00:00:51,120 +que cet objet soit + +63 +00:00:51,120 --> 00:00:52,420 +inédit induit que + +64 +00:00:52,420 --> 00:00:53,660 +notre rapport à lui + +65 +00:00:53,660 --> 00:00:55,000 +est aussi un rapport + +66 +00:00:55,000 --> 00:00:55,460 +inédit? + +67 +00:00:55,460 --> 00:00:56,240 +Je veux dire, + +68 +00:00:56,240 --> 00:00:56,580 +est-ce que le + +69 +00:00:56,580 --> 00:00:57,280 +rapport qu'on a au + +70 +00:00:57,280 --> 00:00:57,920 +smartphone est + +71 +00:00:57,920 --> 00:00:58,660 +comparable à celui + +72 +00:00:58,660 --> 00:00:59,460 +qu'on entretenait à + +73 +00:00:59,460 --> 00:00:59,960 +d'autres objets + +74 +00:00:59,960 --> 00:01:01,500 +techniques comme la + +75 +00:01:01,500 --> 00:01:02,680 +voiture ou le + +76 +00:01:02,680 --> 00:01:03,120 +téléphone? + +77 +00:01:03,360 --> 00:01:05,660 +Il n'y a pas + +78 +00:01:05,660 --> 00:01:06,420 +d'équivalent en + +79 +00:01:06,420 --> 00:01:06,660 +fait. + +80 +00:01:06,880 --> 00:01:07,540 +Et donc cette espèce + +81 +00:01:07,540 --> 00:01:08,940 +de nouveauté dans la + +82 +00:01:08,940 --> 00:01:10,240 +relation à l'objet, + +83 +00:01:10,240 --> 00:01:10,760 +c'est fascinant et + +84 +00:01:10,760 --> 00:01:11,520 +terrifiant. + +85 +00:01:11,620 --> 00:01:12,440 +Parce qu'on a + +86 +00:01:12,440 --> 00:01:13,560 +l'impression, + +87 +00:01:13,560 --> 00:01:14,400 +comme le disent les + +88 +00:01:14,400 --> 00:01:15,000 +utilisateurs et les + +89 +00:01:15,000 --> 00:01:15,220 +services, + +90 +00:01:15,220 --> 00:01:16,080 +d'être dépendants de + +91 +00:01:16,080 --> 00:01:16,480 +cet objet, + +92 +00:01:16,860 --> 00:01:17,340 +d'induire en fait + +93 +00:01:17,340 --> 00:01:18,480 +une espèce de + +94 +00:01:18,480 --> 00:01:18,600 +relation, + +95 +00:01:18,600 --> 00:01:19,920 +de médiation avec le + +96 +00:01:19,920 --> 00:01:21,780 +monde qui rend de + +97 +00:01:21,780 --> 00:01:22,240 +l'ampleur et qui + +98 +00:01:22,240 --> 00:01:22,720 +amène aussi à des + +99 +00:01:22,720 --> 00:01:23,260 +formes de rejet. + +100 +00:01:23,940 --> 00:01:24,940 +Donc, + +101 +00:01:24,940 --> 00:01:26,560 +à objet inédit, + +102 +00:01:26,560 --> 00:01:27,800 +rapport inédit. + +103 +00:01:28,020 --> 00:01:29,280 +Et ce rapport, + +104 +00:01:29,280 --> 00:01:29,880 +si j'en crois + +105 +00:01:29,880 --> 00:01:30,540 +Nicolas, + +106 +00:01:30,540 --> 00:01:31,800 +serait caractérisé + +107 +00:01:31,800 --> 00:01:33,400 +par un mélange de + +108 +00:01:33,400 --> 00:01:34,680 +dépendance et de + +109 +00:01:34,680 --> 00:01:35,140 +rejet. + +110 +00:01:35,780 --> 00:01:37,140 +Bon, en vrai, + +111 +00:01:37,140 --> 00:01:38,080 +il faudrait remonter + +112 +00:01:38,080 --> 00:01:39,320 +très très finement + +113 +00:01:39,320 --> 00:01:40,240 +toute l'histoire des + +114 +00:01:40,240 --> 00:01:41,480 +objets techniques et + +115 +00:01:41,480 --> 00:01:42,320 +de leur insertion + +116 +00:01:42,320 --> 00:01:42,860 +dans nos vies + +117 +00:01:42,900 --> 00:01:43,760 +pour déterminer si + +118 +00:01:43,760 --> 00:01:44,740 +ce rapport est + +119 +00:01:44,740 --> 00:01:45,740 +totalement inédit. + +120 +00:01:46,100 --> 00:01:46,920 +Mais j'ai + +121 +00:01:46,920 --> 00:01:47,560 +l'impression comme + +122 +00:01:47,560 --> 00:01:48,700 +ça que Nicolas ne se + +123 +00:01:48,700 --> 00:01:49,340 +trompe pas vraiment. + +124 +00:01:49,880 --> 00:01:50,520 +Pour autant que je + +125 +00:01:50,520 --> 00:01:51,140 +sache, + +126 +00:01:51,140 --> 00:01:52,060 +il y a eu plein de + +127 +00:01:52,060 --> 00:01:52,940 +discussions autour + +128 +00:01:52,940 --> 00:01:54,060 +de la voiture ou + +129 +00:01:54,060 --> 00:01:54,980 +même du téléphone. + +130 +00:01:55,340 --> 00:01:56,400 +Mais la dépendance + +131 +00:01:56,400 --> 00:01:57,460 +n'était pas du même + +132 +00:01:57,460 --> 00:01:57,780 +ordre. + +133 +00:01:57,780 --> 00:01:58,780 +Donc le rejet non + +134 +00:01:58,780 --> 00:01:59,380 +plus n'était pas du + +135 +00:01:59,380 --> 00:01:59,840 +même ordre. + +136 +00:01:59,980 --> 00:02:00,880 +On peut adorer sa + +137 +00:02:00,880 --> 00:02:01,460 +bagnole, + +138 +00:02:01,460 --> 00:02:02,340 +en avoir besoin pour + +139 +00:02:02,340 --> 00:02:03,020 +plein de choses. + +140 +00:02:03,280 --> 00:02:04,680 +Et bien, le soir, + +141 +00:02:04,680 --> 00:02:05,380 +quand on va se + +142 +00:02:05,380 --> 00:02:05,800 +coucher, + +143 +00:02:05,800 --> 00:02:06,360 +on la laisse. + +144 +00:02:06,980 --> 00:02:07,800 +On ne l'a pas dans + +145 +00:02:07,800 --> 00:02:08,680 +la main quand on est + +146 +00:02:08,680 --> 00:02:09,140 +au lit, + +147 +00:02:09,140 --> 00:02:09,680 +on ne l'emmène pas + +148 +00:02:09,680 --> 00:02:10,480 +au chiottes. + +149 +00:02:10,860 --> 00:02:11,480 +On pouvait être + +150 +00:02:11,480 --> 00:02:13,100 +énervé par son môme + +151 +00:02:13,100 --> 00:02:13,800 +qui occupait la + +152 +00:02:13,800 --> 00:02:14,600 +ligne de téléphone + +153 +00:02:14,600 --> 00:02:15,360 +pendant une heure + +154 +00:02:15,360 --> 00:02:15,960 +chaque soir pour + +155 +00:02:15,960 --> 00:02:16,600 +discuter avec un + +156 +00:02:16,600 --> 00:02:16,900 +copain. + +157 +00:02:17,280 --> 00:02:17,940 +Mais ça ne + +158 +00:02:17,940 --> 00:02:18,980 +ressemblait pas à ce + +159 +00:02:18,980 --> 00:02:20,120 +qu'on peut ressentir + +160 +00:02:20,120 --> 00:02:21,340 +à voir ce même môme + +161 +00:02:21,340 --> 00:02:21,880 +aujourd'hui, + +162 +00:02:22,140 --> 00:02:23,180 +continuellement avec + +163 +00:02:23,180 --> 00:02:23,940 +son smartphone dans + +164 +00:02:23,940 --> 00:02:24,360 +la main, + +165 +00:02:24,360 --> 00:02:25,060 +comme si c'était une + +166 +00:02:25,060 --> 00:02:25,820 +sorte de pacemaker + +167 +00:02:25,820 --> 00:02:26,300 +externe, + +168 +00:02:26,340 --> 00:02:27,360 +comme si le lâcher + +169 +00:02:27,360 --> 00:02:28,000 +allait entraîner sa + +170 +00:02:28,000 --> 00:02:28,840 +mort immédiate. + +171 +00:02:29,040 --> 00:02:29,280 +Bon, + +172 +00:02:29,280 --> 00:02:29,880 +je dis ça pour le + +173 +00:02:29,880 --> 00:02:30,320 +môme, + +174 +00:02:30,320 --> 00:02:31,140 +mais c'est évidemment + +175 +00:02:31,140 --> 00:02:31,760 +valable pour nous + +176 +00:02:31,760 --> 00:02:31,960 +aussi. + +177 +00:02:32,340 --> 00:02:33,460 +Donc, + +178 +00:02:33,460 --> 00:02:34,240 +rapport inédit. + +179 +00:02:34,240 --> 00:02:35,480 +D'accord. + +180 +00:02:35,480 --> 00:02:36,680 +Mais pourquoi a-t-on + +181 +00:02:36,680 --> 00:02:37,260 +l'impression qu'on + +182 +00:02:37,260 --> 00:02:38,220 +n'en sortira jamais? + +183 +00:02:38,860 --> 00:02:39,780 +Est-ce qu'il faut en + +184 +00:02:39,780 --> 00:02:40,660 +remettre la faute + +185 +00:02:40,660 --> 00:02:41,720 +sur les gens qui ont + +186 +00:02:41,720 --> 00:02:42,780 +créé cet outil + +187 +00:02:42,780 --> 00:02:43,500 +merveilleux et + +188 +00:02:43,500 --> 00:02:43,860 +diabolique, + +189 +00:02:43,860 --> 00:02:44,660 +et diabolique parce + +190 +00:02:44,660 --> 00:02:45,320 +que merveilleux? + +191 +00:02:46,340 --> 00:02:47,480 +Les économistes + +192 +00:02:47,480 --> 00:02:47,820 +parlent de + +193 +00:02:47,820 --> 00:02:48,500 +dépendance du + +194 +00:02:48,500 --> 00:02:48,820 +sentier. + +195 +00:02:48,860 --> 00:02:49,700 +C'est l'idée qu'on + +196 +00:02:49,700 --> 00:02:50,780 +est sur un sentier + +197 +00:02:50,780 --> 00:02:51,900 +qui a été établi, + +198 +00:02:51,900 --> 00:02:52,720 +soit volontairement + +199 +00:02:52,720 --> 00:02:54,240 +en marchant dessus, + +200 +00:02:54,240 --> 00:02:55,500 +soit en définissant + +201 +00:02:55,500 --> 00:02:56,040 +des bornes, + +202 +00:02:56,040 --> 00:02:56,820 +en définissant une + +203 +00:02:56,820 --> 00:02:57,420 +signalétique. + diff --git a/tests/expected/split_subtitles/smartphone.mp3_20.vtt b/tests/expected/split_subtitles/smartphone.mp3_20.vtt new file mode 100644 index 0000000000000000000000000000000000000000..b880a5ca949532022a422bc316c7efd245866555 --- /dev/null +++ b/tests/expected/split_subtitles/smartphone.mp3_20.vtt @@ -0,0 +1,611 @@ +WEBVTT + +00:00.380 --> 00:01.080 +C'est évident ce que + +00:01.080 --> 00:01.780 +dit Nicolas, + +00:01.780 --> 00:02.380 +mais je ne me + +00:02.380 --> 00:02.840 +l'étais jamais + +00:02.840 --> 00:03.620 +formulé comme ça. + +00:04.080 --> 00:05.000 +Ce qui fait la force + +00:05.000 --> 00:05.880 +du smartphone, + +00:05.880 --> 00:06.520 +c'est pas seulement + +00:06.520 --> 00:07.560 +l'accumulation des + +00:07.560 --> 00:07.920 +fonctions, + +00:08.320 --> 00:09.100 +mais la manière dont + +00:09.100 --> 00:10.320 +elles interagissent + +00:10.320 --> 00:10.880 +entre elles. + +00:10.960 --> 00:11.400 +Ce qui dit + +00:11.400 --> 00:11.780 +d'ailleurs sur la + +00:11.780 --> 00:12.120 +photo, + +00:12.120 --> 00:13.000 +c'est hyper convaincant. + +00:13.340 --> 00:14.340 +Alors évidemment, + +00:14.340 --> 00:15.160 +il faudrait ajouter + +00:15.160 --> 00:16.020 +les interfaces. + +00:16.220 --> 00:17.260 +L'écran tactile a + +00:17.260 --> 00:18.620 +été beaucoup très + +00:18.620 --> 00:19.360 +souvent mentionné. + +00:19.840 --> 00:20.520 +Mais bon, + +00:20.520 --> 00:20.960 +il faut dire qu'il + +00:20.960 --> 00:22.100 +profite aussi de 20 + +00:22.100 --> 00:22.920 +ans pendant lesquels + +00:22.920 --> 00:23.720 +les ordinateurs nous + +00:23.720 --> 00:24.500 +ont appris à cliquer + +00:24.500 --> 00:25.260 +sur des icônes. + +00:25.420 --> 00:26.660 +Sauf que le + +00:26.660 --> 00:27.620 +smartphone ajoute le + +00:27.620 --> 00:28.180 +toucher, + +00:28.180 --> 00:28.680 +ce qui rend le + +00:28.680 --> 00:30.220 +contact plus direct, + +00:30.220 --> 00:30.640 +plus sensible. + +00:31.040 --> 00:31.700 +Et puis évidemment, + +00:31.700 --> 00:32.120 +il faudrait parler + +00:32.120 --> 00:32.480 +aussi des + +00:32.480 --> 00:33.180 +applications qui + +00:33.180 --> 00:33.960 +permettent de + +00:33.960 --> 00:34.800 +contourner le côté + +00:34.800 --> 00:35.780 +touffu de la + +00:35.780 --> 00:36.780 +navigation web pour + +00:36.780 --> 00:37.680 +aller directement au + +00:37.680 --> 00:37.820 +but. + +00:37.820 --> 00:39.420 +Bref, tout ça, + +00:39.420 --> 00:40.160 +ce sont les + +00:40.160 --> 00:40.960 +conditions qui + +00:40.960 --> 00:42.060 +permettent de créer + +00:42.060 --> 00:42.800 +cet objet dont + +00:42.800 --> 00:43.700 +Nicolas dit qu'il + +00:43.700 --> 00:43.880 +est + +00:43.880 --> 00:44.980 +vraisemblablement + +00:44.980 --> 00:45.700 +inédit dans + +00:45.700 --> 00:46.180 +l'histoire de + +00:46.180 --> 00:46.580 +l'humanité. + +00:46.600 --> 00:47.720 +Mais ça, + +00:47.720 --> 00:48.260 +ça soulève une autre + +00:48.260 --> 00:48.820 +interrogation. + +00:49.220 --> 00:49.980 +Est-ce que le fait + +00:49.980 --> 00:51.120 +que cet objet soit + +00:51.120 --> 00:52.420 +inédit induit que + +00:52.420 --> 00:53.660 +notre rapport à lui + +00:53.660 --> 00:55.000 +est aussi un rapport + +00:55.000 --> 00:55.460 +inédit? + +00:55.460 --> 00:56.240 +Je veux dire, + +00:56.240 --> 00:56.580 +est-ce que le + +00:56.580 --> 00:57.280 +rapport qu'on a au + +00:57.280 --> 00:57.920 +smartphone est + +00:57.920 --> 00:58.660 +comparable à celui + +00:58.660 --> 00:59.460 +qu'on entretenait à + +00:59.460 --> 00:59.960 +d'autres objets + +00:59.960 --> 01:01.500 +techniques comme la + +01:01.500 --> 01:02.680 +voiture ou le + +01:02.680 --> 01:03.120 +téléphone? + +01:03.360 --> 01:05.660 +Il n'y a pas + +01:05.660 --> 01:06.420 +d'équivalent en + +01:06.420 --> 01:06.660 +fait. + +01:06.880 --> 01:07.540 +Et donc cette espèce + +01:07.540 --> 01:08.940 +de nouveauté dans la + +01:08.940 --> 01:10.240 +relation à l'objet, + +01:10.240 --> 01:10.760 +c'est fascinant et + +01:10.760 --> 01:11.520 +terrifiant. + +01:11.620 --> 01:12.440 +Parce qu'on a + +01:12.440 --> 01:13.560 +l'impression, + +01:13.560 --> 01:14.400 +comme le disent les + +01:14.400 --> 01:15.000 +utilisateurs et les + +01:15.000 --> 01:15.220 +services, + +01:15.220 --> 01:16.080 +d'être dépendants de + +01:16.080 --> 01:16.480 +cet objet, + +01:16.860 --> 01:17.340 +d'induire en fait + +01:17.340 --> 01:18.480 +une espèce de + +01:18.480 --> 01:18.600 +relation, + +01:18.600 --> 01:19.920 +de médiation avec le + +01:19.920 --> 01:21.780 +monde qui rend de + +01:21.780 --> 01:22.240 +l'ampleur et qui + +01:22.240 --> 01:22.720 +amène aussi à des + +01:22.720 --> 01:23.260 +formes de rejet. + +01:23.940 --> 01:24.940 +Donc, + +01:24.940 --> 01:26.560 +à objet inédit, + +01:26.560 --> 01:27.800 +rapport inédit. + +01:28.020 --> 01:29.280 +Et ce rapport, + +01:29.280 --> 01:29.880 +si j'en crois + +01:29.880 --> 01:30.540 +Nicolas, + +01:30.540 --> 01:31.800 +serait caractérisé + +01:31.800 --> 01:33.400 +par un mélange de + +01:33.400 --> 01:34.680 +dépendance et de + +01:34.680 --> 01:35.140 +rejet. + +01:35.780 --> 01:37.140 +Bon, en vrai, + +01:37.140 --> 01:38.080 +il faudrait remonter + +01:38.080 --> 01:39.320 +très très finement + +01:39.320 --> 01:40.240 +toute l'histoire des + +01:40.240 --> 01:41.480 +objets techniques et + +01:41.480 --> 01:42.320 +de leur insertion + +01:42.320 --> 01:42.860 +dans nos vies + +01:42.900 --> 01:43.760 +pour déterminer si + +01:43.760 --> 01:44.740 +ce rapport est + +01:44.740 --> 01:45.740 +totalement inédit. + +01:46.100 --> 01:46.920 +Mais j'ai + +01:46.920 --> 01:47.560 +l'impression comme + +01:47.560 --> 01:48.700 +ça que Nicolas ne se + +01:48.700 --> 01:49.340 +trompe pas vraiment. + +01:49.880 --> 01:50.520 +Pour autant que je + +01:50.520 --> 01:51.140 +sache, + +01:51.140 --> 01:52.060 +il y a eu plein de + +01:52.060 --> 01:52.940 +discussions autour + +01:52.940 --> 01:54.060 +de la voiture ou + +01:54.060 --> 01:54.980 +même du téléphone. + +01:55.340 --> 01:56.400 +Mais la dépendance + +01:56.400 --> 01:57.460 +n'était pas du même + +01:57.460 --> 01:57.780 +ordre. + +01:57.780 --> 01:58.780 +Donc le rejet non + +01:58.780 --> 01:59.380 +plus n'était pas du + +01:59.380 --> 01:59.840 +même ordre. + +01:59.980 --> 02:00.880 +On peut adorer sa + +02:00.880 --> 02:01.460 +bagnole, + +02:01.460 --> 02:02.340 +en avoir besoin pour + +02:02.340 --> 02:03.020 +plein de choses. + +02:03.280 --> 02:04.680 +Et bien, le soir, + +02:04.680 --> 02:05.380 +quand on va se + +02:05.380 --> 02:05.800 +coucher, + +02:05.800 --> 02:06.360 +on la laisse. + +02:06.980 --> 02:07.800 +On ne l'a pas dans + +02:07.800 --> 02:08.680 +la main quand on est + +02:08.680 --> 02:09.140 +au lit, + +02:09.140 --> 02:09.680 +on ne l'emmène pas + +02:09.680 --> 02:10.480 +au chiottes. + +02:10.860 --> 02:11.480 +On pouvait être + +02:11.480 --> 02:13.100 +énervé par son môme + +02:13.100 --> 02:13.800 +qui occupait la + +02:13.800 --> 02:14.600 +ligne de téléphone + +02:14.600 --> 02:15.360 +pendant une heure + +02:15.360 --> 02:15.960 +chaque soir pour + +02:15.960 --> 02:16.600 +discuter avec un + +02:16.600 --> 02:16.900 +copain. + +02:17.280 --> 02:17.940 +Mais ça ne + +02:17.940 --> 02:18.980 +ressemblait pas à ce + +02:18.980 --> 02:20.120 +qu'on peut ressentir + +02:20.120 --> 02:21.340 +à voir ce même môme + +02:21.340 --> 02:21.880 +aujourd'hui, + +02:22.140 --> 02:23.180 +continuellement avec + +02:23.180 --> 02:23.940 +son smartphone dans + +02:23.940 --> 02:24.360 +la main, + +02:24.360 --> 02:25.060 +comme si c'était une + +02:25.060 --> 02:25.820 +sorte de pacemaker + +02:25.820 --> 02:26.300 +externe, + +02:26.340 --> 02:27.360 +comme si le lâcher + +02:27.360 --> 02:28.000 +allait entraîner sa + +02:28.000 --> 02:28.840 +mort immédiate. + +02:29.040 --> 02:29.280 +Bon, + +02:29.280 --> 02:29.880 +je dis ça pour le + +02:29.880 --> 02:30.320 +môme, + +02:30.320 --> 02:31.140 +mais c'est évidemment + +02:31.140 --> 02:31.760 +valable pour nous + +02:31.760 --> 02:31.960 +aussi. + +02:32.340 --> 02:33.460 +Donc, + +02:33.460 --> 02:34.240 +rapport inédit. + +02:34.240 --> 02:35.480 +D'accord. + +02:35.480 --> 02:36.680 +Mais pourquoi a-t-on + +02:36.680 --> 02:37.260 +l'impression qu'on + +02:37.260 --> 02:38.220 +n'en sortira jamais? + +02:38.860 --> 02:39.780 +Est-ce qu'il faut en + +02:39.780 --> 02:40.660 +remettre la faute + +02:40.660 --> 02:41.720 +sur les gens qui ont + +02:41.720 --> 02:42.780 +créé cet outil + +02:42.780 --> 02:43.500 +merveilleux et + +02:43.500 --> 02:43.860 +diabolique, + +02:43.860 --> 02:44.660 +et diabolique parce + +02:44.660 --> 02:45.320 +que merveilleux? + +02:46.340 --> 02:47.480 +Les économistes + +02:47.480 --> 02:47.820 +parlent de + +02:47.820 --> 02:48.500 +dépendance du + +02:48.500 --> 02:48.820 +sentier. + +02:48.860 --> 02:49.700 +C'est l'idée qu'on + +02:49.700 --> 02:50.780 +est sur un sentier + +02:50.780 --> 02:51.900 +qui a été établi, + +02:51.900 --> 02:52.720 +soit volontairement + +02:52.720 --> 02:54.240 +en marchant dessus, + +02:54.240 --> 02:55.500 +soit en définissant + +02:55.500 --> 02:56.040 +des bornes, + +02:56.040 --> 02:56.820 +en définissant une + +02:56.820 --> 02:57.420 +signalétique. + diff --git a/tests/expected/split_subtitles/smartphone.mp3_50.srt b/tests/expected/split_subtitles/smartphone.mp3_50.srt new file mode 100644 index 0000000000000000000000000000000000000000..5a9cbd960d9a7073f91c8d0412e7daf0f797d25c --- /dev/null +++ b/tests/expected/split_subtitles/smartphone.mp3_50.srt @@ -0,0 +1,356 @@ +1 +00:00:00,380 --> 00:00:01,780 +C'est évident ce que dit Nicolas, + +2 +00:00:01,780 --> 00:00:03,620 +mais je ne me l'étais jamais formulé comme ça. + +3 +00:00:04,080 --> 00:00:05,880 +Ce qui fait la force du smartphone, + +4 +00:00:05,880 --> 00:00:07,920 +c'est pas seulement l'accumulation des fonctions, + +5 +00:00:08,320 --> 00:00:10,580 +mais la manière dont elles interagissent entre + +6 +00:00:10,580 --> 00:00:10,880 +elles. + +7 +00:00:10,960 --> 00:00:12,120 +Ce qui dit d'ailleurs sur la photo, + +8 +00:00:12,120 --> 00:00:13,000 +c'est hyper convaincant. + +9 +00:00:13,340 --> 00:00:14,340 +Alors évidemment, + +10 +00:00:14,340 --> 00:00:16,020 +il faudrait ajouter les interfaces. + +11 +00:00:16,220 --> 00:00:18,900 +L'écran tactile a été beaucoup très souvent + +12 +00:00:18,900 --> 00:00:19,360 +mentionné. + +13 +00:00:19,840 --> 00:00:20,520 +Mais bon, + +14 +00:00:20,520 --> 00:00:22,480 +il faut dire qu'il profite aussi de 20 ans pendant + +15 +00:00:22,480 --> 00:00:24,500 +lesquels les ordinateurs nous ont appris à cliquer + +16 +00:00:24,500 --> 00:00:25,260 +sur des icônes. + +17 +00:00:25,420 --> 00:00:28,180 +Sauf que le smartphone ajoute le toucher, + +18 +00:00:28,180 --> 00:00:30,640 +ce qui rend le contact plus direct, plus sensible. + +19 +00:00:31,040 --> 00:00:31,700 +Et puis évidemment, + +20 +00:00:31,700 --> 00:00:33,180 +il faudrait parler aussi des applications qui + +21 +00:00:33,180 --> 00:00:35,780 +permettent de contourner le côté touffu de la + +22 +00:00:35,780 --> 00:00:37,820 +navigation web pour aller directement au but. + +23 +00:00:37,820 --> 00:00:39,420 +Bref, tout ça, + +24 +00:00:39,420 --> 00:00:42,380 +ce sont les conditions qui permettent de créer cet + +25 +00:00:42,380 --> 00:00:44,980 +objet dont Nicolas dit qu'il est vraisemblablement + +26 +00:00:44,980 --> 00:00:46,580 +inédit dans l'histoire de l'humanité. + +27 +00:00:46,600 --> 00:00:48,820 +Mais ça, ça soulève une autre interrogation. + +28 +00:00:49,220 --> 00:00:51,800 +Est-ce que le fait que cet objet soit inédit + +29 +00:00:51,800 --> 00:00:54,700 +induit que notre rapport à lui est aussi un + +30 +00:00:54,700 --> 00:00:55,460 +rapport inédit? + +31 +00:00:55,460 --> 00:00:56,240 +Je veux dire, + +32 +00:00:56,240 --> 00:00:57,920 +est-ce que le rapport qu'on a au smartphone est + +33 +00:00:57,920 --> 00:00:59,700 +comparable à celui qu'on entretenait à d'autres + +34 +00:00:59,700 --> 00:01:02,680 +objets techniques comme la voiture ou le + +35 +00:01:02,680 --> 00:01:03,120 +téléphone? + +36 +00:01:03,360 --> 00:01:06,660 +Il n'y a pas d'équivalent en fait. + +37 +00:01:06,880 --> 00:01:09,220 +Et donc cette espèce de nouveauté dans la relation + +38 +00:01:09,220 --> 00:01:11,520 +à l'objet, c'est fascinant et terrifiant. + +39 +00:01:11,620 --> 00:01:13,560 +Parce qu'on a l'impression, + +40 +00:01:13,560 --> 00:01:15,220 +comme le disent les utilisateurs et les services, + +41 +00:01:15,220 --> 00:01:16,480 +d'être dépendants de cet objet, + +42 +00:01:16,860 --> 00:01:18,600 +d'induire en fait une espèce de relation, + +43 +00:01:18,600 --> 00:01:22,020 +de médiation avec le monde qui rend de l'ampleur + +44 +00:01:22,020 --> 00:01:23,260 +et qui amène aussi à des formes de rejet. + +45 +00:01:23,940 --> 00:01:27,800 +Donc, à objet inédit, rapport inédit. + +46 +00:01:28,020 --> 00:01:30,540 +Et ce rapport, si j'en crois Nicolas, + +47 +00:01:30,540 --> 00:01:34,540 +serait caractérisé par un mélange de dépendance et + +48 +00:01:34,540 --> 00:01:35,140 +de rejet. + +49 +00:01:35,780 --> 00:01:37,140 +Bon, en vrai, + +50 +00:01:37,140 --> 00:01:39,700 +il faudrait remonter très très finement toute + +51 +00:01:39,700 --> 00:01:41,840 +l'histoire des objets techniques et de leur + +52 +00:01:41,840 --> 00:01:42,860 +insertion dans nos vies + +53 +00:01:42,900 --> 00:01:45,300 +pour déterminer si ce rapport est totalement + +54 +00:01:45,300 --> 00:01:45,740 +inédit. + +55 +00:01:46,100 --> 00:01:48,700 +Mais j'ai l'impression comme ça que Nicolas ne se + +56 +00:01:48,700 --> 00:01:49,340 +trompe pas vraiment. + +57 +00:01:49,880 --> 00:01:51,140 +Pour autant que je sache, + +58 +00:01:51,140 --> 00:01:53,520 +il y a eu plein de discussions autour de la + +59 +00:01:53,520 --> 00:01:54,980 +voiture ou même du téléphone. + +60 +00:01:55,340 --> 00:01:57,780 +Mais la dépendance n'était pas du même ordre. + +61 +00:01:57,780 --> 00:01:59,840 +Donc le rejet non plus n'était pas du même ordre. + +62 +00:01:59,980 --> 00:02:01,460 +On peut adorer sa bagnole, + +63 +00:02:01,460 --> 00:02:03,020 +en avoir besoin pour plein de choses. + +64 +00:02:03,280 --> 00:02:05,800 +Et bien, le soir, quand on va se coucher, + +65 +00:02:05,800 --> 00:02:06,360 +on la laisse. + +66 +00:02:06,980 --> 00:02:09,140 +On ne l'a pas dans la main quand on est au lit, + +67 +00:02:09,140 --> 00:02:10,480 +on ne l'emmène pas au chiottes. + +68 +00:02:10,860 --> 00:02:13,760 +On pouvait être énervé par son môme qui occupait + +69 +00:02:13,760 --> 00:02:15,540 +la ligne de téléphone pendant une heure chaque + +70 +00:02:15,540 --> 00:02:16,900 +soir pour discuter avec un copain. + +71 +00:02:17,280 --> 00:02:19,480 +Mais ça ne ressemblait pas à ce qu'on peut + +72 +00:02:19,480 --> 00:02:21,880 +ressentir à voir ce même môme aujourd'hui, + +73 +00:02:22,140 --> 00:02:24,360 +continuellement avec son smartphone dans la main, + +74 +00:02:24,360 --> 00:02:26,300 +comme si c'était une sorte de pacemaker externe, + +75 +00:02:26,340 --> 00:02:28,220 +comme si le lâcher allait entraîner sa mort + +76 +00:02:28,220 --> 00:02:28,840 +immédiate. + +77 +00:02:29,040 --> 00:02:30,320 +Bon, je dis ça pour le môme, + +78 +00:02:30,320 --> 00:02:31,960 +mais c'est évidemment valable pour nous aussi. + +79 +00:02:32,340 --> 00:02:35,480 +Donc, rapport inédit. D'accord. + +80 +00:02:35,480 --> 00:02:37,440 +Mais pourquoi a-t-on l'impression qu'on n'en + +81 +00:02:37,440 --> 00:02:38,220 +sortira jamais? + +82 +00:02:38,860 --> 00:02:41,280 +Est-ce qu'il faut en remettre la faute sur les + +83 +00:02:41,280 --> 00:02:43,500 +gens qui ont créé cet outil merveilleux et + +84 +00:02:43,500 --> 00:02:45,320 +diabolique, et diabolique parce que merveilleux? + +85 +00:02:46,340 --> 00:02:48,820 +Les économistes parlent de dépendance du sentier. + +86 +00:02:48,860 --> 00:02:51,120 +C'est l'idée qu'on est sur un sentier qui a été + +87 +00:02:51,120 --> 00:02:54,240 +établi, soit volontairement en marchant dessus, + +88 +00:02:54,240 --> 00:02:56,040 +soit en définissant des bornes, + +89 +00:02:56,040 --> 00:02:57,420 +en définissant une signalétique. + diff --git a/tests/expected/split_subtitles/smartphone.mp3_50.vtt b/tests/expected/split_subtitles/smartphone.mp3_50.vtt new file mode 100644 index 0000000000000000000000000000000000000000..68d9b01306781ba2fcb81166b675053824255222 --- /dev/null +++ b/tests/expected/split_subtitles/smartphone.mp3_50.vtt @@ -0,0 +1,269 @@ +WEBVTT + +00:00.380 --> 00:01.780 +C'est évident ce que dit Nicolas, + +00:01.780 --> 00:03.620 +mais je ne me l'étais jamais formulé comme ça. + +00:04.080 --> 00:05.880 +Ce qui fait la force du smartphone, + +00:05.880 --> 00:07.920 +c'est pas seulement l'accumulation des fonctions, + +00:08.320 --> 00:10.580 +mais la manière dont elles interagissent entre + +00:10.580 --> 00:10.880 +elles. + +00:10.960 --> 00:12.120 +Ce qui dit d'ailleurs sur la photo, + +00:12.120 --> 00:13.000 +c'est hyper convaincant. + +00:13.340 --> 00:14.340 +Alors évidemment, + +00:14.340 --> 00:16.020 +il faudrait ajouter les interfaces. + +00:16.220 --> 00:18.900 +L'écran tactile a été beaucoup très souvent + +00:18.900 --> 00:19.360 +mentionné. + +00:19.840 --> 00:20.520 +Mais bon, + +00:20.520 --> 00:22.480 +il faut dire qu'il profite aussi de 20 ans pendant + +00:22.480 --> 00:24.500 +lesquels les ordinateurs nous ont appris à cliquer + +00:24.500 --> 00:25.260 +sur des icônes. + +00:25.420 --> 00:28.180 +Sauf que le smartphone ajoute le toucher, + +00:28.180 --> 00:30.640 +ce qui rend le contact plus direct, plus sensible. + +00:31.040 --> 00:31.700 +Et puis évidemment, + +00:31.700 --> 00:33.180 +il faudrait parler aussi des applications qui + +00:33.180 --> 00:35.780 +permettent de contourner le côté touffu de la + +00:35.780 --> 00:37.820 +navigation web pour aller directement au but. + +00:37.820 --> 00:39.420 +Bref, tout ça, + +00:39.420 --> 00:42.380 +ce sont les conditions qui permettent de créer cet + +00:42.380 --> 00:44.980 +objet dont Nicolas dit qu'il est vraisemblablement + +00:44.980 --> 00:46.580 +inédit dans l'histoire de l'humanité. + +00:46.600 --> 00:48.820 +Mais ça, ça soulève une autre interrogation. + +00:49.220 --> 00:51.800 +Est-ce que le fait que cet objet soit inédit + +00:51.800 --> 00:54.700 +induit que notre rapport à lui est aussi un + +00:54.700 --> 00:55.460 +rapport inédit? + +00:55.460 --> 00:56.240 +Je veux dire, + +00:56.240 --> 00:57.920 +est-ce que le rapport qu'on a au smartphone est + +00:57.920 --> 00:59.700 +comparable à celui qu'on entretenait à d'autres + +00:59.700 --> 01:02.680 +objets techniques comme la voiture ou le + +01:02.680 --> 01:03.120 +téléphone? + +01:03.360 --> 01:06.660 +Il n'y a pas d'équivalent en fait. + +01:06.880 --> 01:09.220 +Et donc cette espèce de nouveauté dans la relation + +01:09.220 --> 01:11.520 +à l'objet, c'est fascinant et terrifiant. + +01:11.620 --> 01:13.560 +Parce qu'on a l'impression, + +01:13.560 --> 01:15.220 +comme le disent les utilisateurs et les services, + +01:15.220 --> 01:16.480 +d'être dépendants de cet objet, + +01:16.860 --> 01:18.600 +d'induire en fait une espèce de relation, + +01:18.600 --> 01:22.020 +de médiation avec le monde qui rend de l'ampleur + +01:22.020 --> 01:23.260 +et qui amène aussi à des formes de rejet. + +01:23.940 --> 01:27.800 +Donc, à objet inédit, rapport inédit. + +01:28.020 --> 01:30.540 +Et ce rapport, si j'en crois Nicolas, + +01:30.540 --> 01:34.540 +serait caractérisé par un mélange de dépendance et + +01:34.540 --> 01:35.140 +de rejet. + +01:35.780 --> 01:37.140 +Bon, en vrai, + +01:37.140 --> 01:39.700 +il faudrait remonter très très finement toute + +01:39.700 --> 01:41.840 +l'histoire des objets techniques et de leur + +01:41.840 --> 01:42.860 +insertion dans nos vies + +01:42.900 --> 01:45.300 +pour déterminer si ce rapport est totalement + +01:45.300 --> 01:45.740 +inédit. + +01:46.100 --> 01:48.700 +Mais j'ai l'impression comme ça que Nicolas ne se + +01:48.700 --> 01:49.340 +trompe pas vraiment. + +01:49.880 --> 01:51.140 +Pour autant que je sache, + +01:51.140 --> 01:53.520 +il y a eu plein de discussions autour de la + +01:53.520 --> 01:54.980 +voiture ou même du téléphone. + +01:55.340 --> 01:57.780 +Mais la dépendance n'était pas du même ordre. + +01:57.780 --> 01:59.840 +Donc le rejet non plus n'était pas du même ordre. + +01:59.980 --> 02:01.460 +On peut adorer sa bagnole, + +02:01.460 --> 02:03.020 +en avoir besoin pour plein de choses. + +02:03.280 --> 02:05.800 +Et bien, le soir, quand on va se coucher, + +02:05.800 --> 02:06.360 +on la laisse. + +02:06.980 --> 02:09.140 +On ne l'a pas dans la main quand on est au lit, + +02:09.140 --> 02:10.480 +on ne l'emmène pas au chiottes. + +02:10.860 --> 02:13.760 +On pouvait être énervé par son môme qui occupait + +02:13.760 --> 02:15.540 +la ligne de téléphone pendant une heure chaque + +02:15.540 --> 02:16.900 +soir pour discuter avec un copain. + +02:17.280 --> 02:19.480 +Mais ça ne ressemblait pas à ce qu'on peut + +02:19.480 --> 02:21.880 +ressentir à voir ce même môme aujourd'hui, + +02:22.140 --> 02:24.360 +continuellement avec son smartphone dans la main, + +02:24.360 --> 02:26.300 +comme si c'était une sorte de pacemaker externe, + +02:26.340 --> 02:28.220 +comme si le lâcher allait entraîner sa mort + +02:28.220 --> 02:28.840 +immédiate. + +02:29.040 --> 02:30.320 +Bon, je dis ça pour le môme, + +02:30.320 --> 02:31.960 +mais c'est évidemment valable pour nous aussi. + +02:32.340 --> 02:35.480 +Donc, rapport inédit. D'accord. + +02:35.480 --> 02:37.440 +Mais pourquoi a-t-on l'impression qu'on n'en + +02:37.440 --> 02:38.220 +sortira jamais? + +02:38.860 --> 02:41.280 +Est-ce qu'il faut en remettre la faute sur les + +02:41.280 --> 02:43.500 +gens qui ont créé cet outil merveilleux et + +02:43.500 --> 02:45.320 +diabolique, et diabolique parce que merveilleux? + +02:46.340 --> 02:48.820 +Les économistes parlent de dépendance du sentier. + +02:48.860 --> 02:51.120 +C'est l'idée qu'on est sur un sentier qui a été + +02:51.120 --> 02:54.240 +établi, soit volontairement en marchant dessus, + +02:54.240 --> 02:56.040 +soit en définissant des bornes, + +02:56.040 --> 02:57.420 +en définissant une signalétique. + diff --git a/tests/expected/split_subtitles/smartphone.mp3_6.srt b/tests/expected/split_subtitles/smartphone.mp3_6.srt new file mode 100644 index 0000000000000000000000000000000000000000..e03246f80d846a479b5404c598c34d50b8266e96 --- /dev/null +++ b/tests/expected/split_subtitles/smartphone.mp3_6.srt @@ -0,0 +1,2024 @@ +1 +00:00:00,380 --> 00:00:00,580 +C'est + +2 +00:00:00,580 --> 00:00:00,880 +évident + +3 +00:00:00,880 --> 00:00:01,080 +ce que + +4 +00:00:01,080 --> 00:00:01,200 +dit + +5 +00:00:01,200 --> 00:00:01,780 +Nicolas, + +6 +00:00:01,780 --> 00:00:01,900 +mais + +7 +00:00:01,900 --> 00:00:02,340 +je ne + +8 +00:00:02,340 --> 00:00:02,380 +me + +9 +00:00:02,380 --> 00:00:02,580 +l'étais + +10 +00:00:02,580 --> 00:00:02,840 +jamais + +11 +00:00:02,840 --> 00:00:03,260 +formulé + +12 +00:00:03,260 --> 00:00:03,420 +comme + +13 +00:00:03,420 --> 00:00:03,620 +ça. + +14 +00:00:04,080 --> 00:00:04,340 +Ce qui + +15 +00:00:04,340 --> 00:00:04,480 +fait + +16 +00:00:04,480 --> 00:00:04,660 +la + +17 +00:00:04,660 --> 00:00:05,000 +force + +18 +00:00:05,000 --> 00:00:05,200 +du + +19 +00:00:05,200 --> 00:00:05,880 +smartphone, + +20 +00:00:05,880 --> 00:00:06,120 +c'est + +21 +00:00:06,120 --> 00:00:06,260 +pas + +22 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00:02:56,820 +une + +506 +00:02:56,820 --> 00:02:57,420 +signalétique. + diff --git a/tests/expected/split_subtitles/smartphone.mp3_6.vtt b/tests/expected/split_subtitles/smartphone.mp3_6.vtt new file mode 100644 index 0000000000000000000000000000000000000000..61871c111372405e0b3331b5d11e0e1cbd3f450e --- /dev/null +++ b/tests/expected/split_subtitles/smartphone.mp3_6.vtt @@ -0,0 +1,1520 @@ +WEBVTT + +00:00.380 --> 00:00.580 +C'est + +00:00.580 --> 00:00.880 +évident + +00:00.880 --> 00:01.080 +ce que + +00:01.080 --> 00:01.200 +dit + +00:01.200 --> 00:01.780 +Nicolas, + +00:01.780 --> 00:01.900 +mais + +00:01.900 --> 00:02.340 +je ne + +00:02.340 --> 00:02.380 +me + +00:02.380 --> 00:02.580 +l'étais + +00:02.580 --> 00:02.840 +jamais + +00:02.840 --> 00:03.260 +formulé + +00:03.260 --> 00:03.420 +comme + +00:03.420 --> 00:03.620 +ça. + +00:04.080 --> 00:04.340 +Ce qui + +00:04.340 --> 00:04.480 +fait + +00:04.480 --> 00:04.660 +la + +00:04.660 --> 00:05.000 +force + +00:05.000 --> 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What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? What are you telling me, dude? 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Mais je me l'étais jamais formulé comme ça. Ce qui fait la force du smartphone, c'est pas seulement la cumulation des fonctions, mais la manière dans quelques interagues entraîne. Et il est d'ailleurs, c'est la photo c'est hyper convaincant. Alors évidemment, il faudrait ajouter les interfaces les grand-attêtes qu'il a été beaucoup très souvent ementionné. Mais bon, il faudrait que les profites aussi de 20 ans pendant l'été, les ordinateurs nous ont appris à piquer sur des icônes. C'est ce que le smartphone ajoute le toucher, qui rend le contact plus direct, plus sensible. Et puis, évidemment, il faudrait parler aussi des applications qui permettent de contourner le côté tout flu de la navigation web pour aller directement en but. Bref, tout ça, ce sont les conditions qui permettent de créer cette objet, en Nicolas, dit qu'il est très fondablement inédit dans l'histoire de l'humanité. Mais ça s'assoulait d'une autre interrogation. Est-ce que le fait que cette objet soit inédit un d'huies que notre rapport a lui est aussi un rapport inédit? Je veux dire, est-ce que le rapport qu'on a au sein de foi n'est comparable à celui qu'on entretenait à d'autres objectes techniques comme la voiture ou le téléphone? Il n'y a pas d'équivalent. On s'est espécie de nous voter dans la relation à l'objet. C'est facilement éterréciant parce qu'on a impression de, comme le 10, les utilisateurs et les efforts, elles aident dépendant de cette objet d'un lieu, en fait, une espèce de relation de médiation avec le monde qui rendent un peu avec la même sédiforme de le jeu. Donc, à objets inédits, rapport inédits. Et, ce rapport, si j'en prends Nicolas, frère caractérisée par un mélange de dépenses et de rojets. Bon, en vrai, il faudrait remonter très très finement toute l'histoire des objectes techniques et de leur infération dans le vie pour déterminer si ce rapport est totalement inédit. Mais j'ai l'impression comme ça que Nicolas se trompe pas vraiment. Pour autant, je sache. Il y a eu plein de discussions autour de la voiture ou même du téléphone. Mais la dépense n'était pas du même mort, donc le rejet n'en plus n'était pas du même mort. On peut adorer sa bagnure, en avoir besoin pour plein de choses. Et là, le soir, quand on va se coucher, on la laisse. On l'a pas dans la main, quand on est collis, quand on n'en mène pas au chiot. On pouvait être émervé par son mome qui occupeait la ligne de téléphone pendant une heure chaque soir pour discuter avec un copain. Mais ça ne ressemble pas à ce qu'on peut ressentir à voir même mome aujourd'hui continuuellement avec son smartphone dans la main, comme c'était une sorte de estimateur extère de l'intempis de lâcher à l'éantrénée, ça m'a eu immédiate. Bon, je dis ça pour le mome, mais évidemment, va là pour nos aussi. Donc, rapport immédiate d'accord. Mais pourquoi, à ton impression qu'on en sortira jamais? Et puis, il faut en remettre la faute sur les gens qui ont créé cette route merveilleux et diabolique, qui a dit à bollique par coeur, merveilleux. Les économistes parlent de dépendance du santé. Ces vidéos, en fait, on est un santé qui a été établie, c'est un soit mon termine, soit définissant des beurs, on définisse un signalétique.", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.42, + "end": 1.38, + "text": " C'est évidence que dit Nicolas.", + "tokens": [ + 383, + 6, + 377, + 20090, + 2778, + 631, + 6176, + 38268, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.566579490710216, + "compression_ratio": 1.605421686746988, + "no_speech_prob": 0.14170263707637787, + "confidence": 0.625, + "words": [ + { + "text": "C'est", + "start": 0.42, + "end": 0.66, + "confidence": 0.849 + }, + { + "text": "évidence", + "start": 0.66, + "end": 0.94, + "confidence": 0.368 + }, + { + "text": "que", + "start": 0.94, + "end": 1.06, + "confidence": 0.883 + }, + { + "text": "dit", + "start": 1.06, + "end": 1.16, + "confidence": 0.344 + }, + { + "text": "Nicolas.", + "start": 1.16, + "end": 1.38, + "confidence": 0.921 + } + ] + }, + { + "id": 1, + "seek": 0, + "start": 1.66, + "end": 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+ "end": 10.84, + "text": " dans quelques interagues entraîne.", + "tokens": [ + 2680, + 16597, + 728, + 559, + 1247, + 22284, + 24741, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.566579490710216, + "compression_ratio": 1.605421686746988, + "no_speech_prob": 0.14170263707637787, + "confidence": 0.3, + "words": [ + { + "text": "dans", + "start": 8.9, + "end": 9.04, + "confidence": 0.329 + }, + { + "text": "quelques", + "start": 9.04, + "end": 9.26, + "confidence": 0.282 + }, + { + "text": "interagues", + "start": 9.26, + "end": 10.18, + "confidence": 0.238 + }, + { + "text": "entraîne.", + "start": 10.18, + "end": 10.84, + "confidence": 0.421 + } + ] + }, + { + "id": 4, + "seek": 0, + "start": 11.04, + "end": 12.92, + "text": " Et il est d'ailleurs, c'est la photo c'est hyper convaincant.", + "tokens": [ + 3790, + 1930, + 871, + 274, + 6, + 19400, + 11, + 269, + 6, + 377, + 635, + 5052, + 269, + 6, + 377, + 9848, + 3754, + 491, + 66, + 394, + 13 + ], + "temperature": 0.0, + 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13, + "seek": 2556, + "start": 43.1, + "end": 46.48, + "text": " dit qu'il est très fondablement inédit dans l'histoire de l'humanité.", + "tokens": [ + 6176, + 421, + 6, + 388, + 871, + 5732, + 9557, + 712, + 518, + 294, + 7811, + 270, + 2680, + 287, + 6, + 29093, + 368, + 287, + 6, + 18796, + 5066, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.4095459938049316, + "compression_ratio": 1.7522658610271904, + "no_speech_prob": 0.0006256799097172916, + "confidence": 0.768, + "words": [ + { + "text": "dit", + "start": 43.1, + "end": 43.52, + "confidence": 0.551 + }, + { + "text": "qu'il", + "start": 43.52, + "end": 43.68, + "confidence": 0.969 + }, + { + "text": "est", + "start": 43.68, + "end": 43.8, + "confidence": 0.851 + }, + { + "text": "très", + "start": 43.8, + "end": 43.94, + "confidence": 0.368 + }, + { + "text": "fondablement", + "start": 43.94, + "end": 44.68, + "confidence": 0.593 + }, + { + "text": "inédit", + "start": 44.68, + "end": 45.52, + "confidence": 0.66 + }, + { 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"start": 55.6, + "end": 58.6, + "text": " Je veux dire, est-ce que le rapport qu'on a au sein de foi n'est comparable à celui", + "tokens": [ + 2588, + 16389, + 1264, + 11, + 871, + 12, + 384, + 631, + 476, + 18018, + 421, + 6, + 266, + 257, + 1609, + 6195, + 368, + 6901, + 297, + 6, + 377, + 6311, + 712, + 1531, + 22829 + ], + "temperature": 0.0, + "avg_logprob": -0.6093524909167556, + "compression_ratio": 1.6292834890965733, + "no_speech_prob": 6.752492481609806e-05, + "confidence": 0.626, + "words": [ + { + "text": "Je", + "start": 55.6, + "end": 55.84, + "confidence": 0.335 + }, + { + "text": "veux", + "start": 55.84, + "end": 55.94, + "confidence": 0.432 + }, + { + "text": "dire,", + "start": 55.94, + "end": 56.16, + "confidence": 0.992 + }, + { + "text": "est-ce", + "start": 56.16, + "end": 56.34, + "confidence": 0.951 + }, + { + "text": "que", + "start": 56.34, + "end": 56.4, + "confidence": 0.973 + }, + { + "text": "le", + "start": 56.4, + "end": 56.54, + "confidence": 0.987 + 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qu'on entretenait à d'autres objectes techniques comme la voiture ou le téléphone?", + "tokens": [ + 421, + 6, + 266, + 3962, + 1147, + 1001, + 1531, + 274, + 6, + 16752, + 2657, + 279, + 7512, + 5173, + 635, + 38859, + 2820, + 476, + 47159, + 2506 + ], + "temperature": 0.0, + "avg_logprob": -0.6093524909167556, + "compression_ratio": 1.6292834890965733, + "no_speech_prob": 6.752492481609806e-05, + "confidence": 0.781, + "words": [ + { + "text": "qu'on", + "start": 58.72, + "end": 58.88, + "confidence": 0.941 + }, + { + "text": "entretenait", + "start": 58.88, + "end": 59.38, + "confidence": 0.657 + }, + { + "text": "à", + "start": 59.38, + "end": 59.44, + "confidence": 0.973 + }, + { + "text": "d'autres", + "start": 59.44, + "end": 59.64, + "confidence": 0.909 + }, + { + "text": "objectes", + "start": 59.64, + "end": 60.02, + "confidence": 0.528 + }, + { + "text": "techniques", + "start": 60.02, + "end": 60.38, + "confidence": 0.547 + }, + { + "text": "comme", + "start": 60.38, + 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+ "id": 24, + "seek": 8298, + "start": 83.0, + "end": 87.66, + "text": " le jeu. Donc, à objets inédits, rapport inédits.", + "tokens": [ + 476, + 16748, + 13, + 7477, + 11, + 1531, + 1111, + 25349, + 294, + 7811, + 1208, + 11, + 18018, + 294, + 7811, + 1208, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.4346100035167876, + "compression_ratio": 1.5907335907335907, + "no_speech_prob": 3.121094050584361e-05, + "confidence": 0.614, + "words": [ + { + "text": "le", + "start": 83.0, + "end": 83.12, + "confidence": 0.128 + }, + { + "text": "jeu.", + "start": 83.12, + "end": 83.64, + "confidence": 0.505 + }, + { + "text": "Donc,", + "start": 83.64, + "end": 84.48, + "confidence": 0.513 + }, + { + "text": "à", + "start": 84.48, + "end": 84.86, + "confidence": 0.634 + }, + { + "text": "objets", + "start": 84.86, + "end": 85.36, + "confidence": 0.547 + }, + { + "text": "inédits,", + "start": 85.36, + "end": 86.24, + "confidence": 0.73 + }, + { + "text": "rapport", + "start": 86.24, + "end": 86.62, + "confidence": 0.928 + }, + { + "text": "inédits.", + "start": 86.62, + "end": 87.66, + "confidence": 0.921 + } + ] + }, + { + "id": 25, + "seek": 8298, + "start": 88.08, + "end": 93.78, + "text": " Et, ce rapport, si j'en prends Nicolas, frère caractérisée par un mélange de dépenses", + "tokens": [ + 3790, + 11, + 1769, + 18018, + 11, + 1511, + 361, + 6, + 268, + 46750, + 38268, + 11, + 431, + 4212, + 1032, + 578, + 4198, + 50027, + 971, + 517, + 41953, + 933, + 368, + 27998, + 9085 + ], + "temperature": 0.0, + "avg_logprob": -0.4346100035167876, + "compression_ratio": 1.5907335907335907, + "no_speech_prob": 3.121094050584361e-05, + "confidence": 0.624, + "words": [ + { + "text": "Et,", + "start": 88.08, + "end": 88.3, + "confidence": 0.87 + }, + { + "text": "ce", + "start": 88.3, + "end": 88.8, + "confidence": 0.462 + }, + { + "text": "rapport,", + "start": 88.8, + "end": 89.28, + "confidence": 0.997 + }, + { + "text": "si", + "start": 89.28, + "end": 89.56, + "confidence": 0.913 + }, + { + "text": "j'en", + "start": 89.56, + "end": 89.74, + 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"dans", + "start": 102.22, + "end": 102.46, + "confidence": 0.518 + }, + { + "text": "le", + "start": 102.46, + "end": 102.54, + "confidence": 0.511 + }, + { + "text": "vie", + "start": 102.54, + "end": 102.78, + "confidence": 0.612 + }, + { + "text": "pour", + "start": 102.78, + "end": 103.06, + "confidence": 0.933 + }, + { + "text": "déterminer", + "start": 103.06, + "end": 103.64, + "confidence": 0.954 + }, + { + "text": "si", + "start": 103.64, + "end": 103.74, + "confidence": 0.488 + }, + { + "text": "ce", + "start": 103.74, + "end": 103.86, + "confidence": 0.98 + }, + { + "text": "rapport", + "start": 103.86, + "end": 104.1, + "confidence": 0.997 + }, + { + "text": "est", + "start": 104.1, + "end": 104.88, + "confidence": 0.942 + }, + { + "text": "totalement", + "start": 104.88, + "end": 105.14, + "confidence": 0.854 + } + ] + }, + { + "id": 29, + "seek": 8298, + "start": 105.26, + "end": 105.78, + "text": " inédit.", + "tokens": [ + 294, + 7811, + 270, + 13 + ], + "temperature": 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Il y a eu plein de discussions autour de la voiture ou même", + "tokens": [ + 8732, + 34081, + 11, + 1506, + 262, + 6000, + 13, + 4416, + 288, + 257, + 2228, + 21088, + 368, + 11088, + 30249, + 368, + 635, + 38859, + 2820, + 5698 + ], + "temperature": 0.0, + "avg_logprob": -0.394765736144266, + "compression_ratio": 1.7249190938511327, + "no_speech_prob": 9.048193533089943e-06, + "confidence": 0.829, + "words": [ + { + "text": "Pour", + "start": 109.72, + "end": 110.08, + "confidence": 0.92 + }, + { + "text": "autant,", + "start": 110.08, + "end": 110.36, + "confidence": 0.986 + }, + { + "text": "je", + "start": 110.36, + "end": 110.4, + "confidence": 0.894 + }, + { + "text": "sache.", + "start": 110.4, + "end": 110.86, + "confidence": 0.531 + }, + { + "text": "Il", + "start": 110.86, + "end": 111.16, + "confidence": 0.851 + }, + { + "text": "y", + "start": 111.16, + "end": 111.22, + "confidence": 0.872 + }, + { + "text": "a", + "start": 111.22, + "end": 111.28, + "confidence": 0.939 + }, + { + "text": "eu", + "start": 111.28, + "end": 111.38, + "confidence": 0.891 + }, + { + "text": "plein", + "start": 111.38, + "end": 111.76, + "confidence": 0.833 + }, + { + "text": "de", + "start": 111.76, + "end": 112.04, + "confidence": 0.94 + }, + { + "text": "discussions", + "start": 112.04, + "end": 112.46, + "confidence": 0.711 + }, + { + "text": "autour", + "start": 112.46, + "end": 112.96, + "confidence": 0.97 + }, + { + "text": "de", + "start": 112.96, + "end": 113.46, + "confidence": 0.952 + }, + { + "text": "la", + "start": 113.46, + "end": 113.5, + "confidence": 0.955 + }, + { + "text": "voiture", + "start": 113.5, + "end": 113.8, + "confidence": 0.983 + }, + { + "text": "ou", + "start": 113.8, + "end": 114.02, + "confidence": 0.523 + }, + { + "text": "même", + "start": 114.02, + "end": 114.26, + "confidence": 0.963 + } + ] + }, + { + "id": 32, + "seek": 10970, + "start": 114.42, + "end": 118.76, + "text": " du téléphone. Mais la dépense n'était pas du même mort, donc le rejet n'en", + "tokens": [ + 1581, + 47159, + 13, + 6313, + 635, + 27998, + 1288, + 297, + 6, + 9743, + 1736, + 1581, + 5698, + 6599, + 11, + 5926, + 476, + 319, + 7108, + 297, + 6, + 268 + ], + "temperature": 0.0, + "avg_logprob": -0.394765736144266, + "compression_ratio": 1.7249190938511327, + "no_speech_prob": 9.048193533089943e-06, + "confidence": 0.732, + "words": [ + { + "text": "du", + "start": 114.42, + "end": 114.6, + "confidence": 0.677 + }, + { + "text": "téléphone.", + "start": 114.6, + "end": 115.16, + "confidence": 0.983 + }, + { + "text": "Mais", + "start": 115.16, + "end": 115.72, + "confidence": 0.649 + }, + { + "text": "la", + "start": 115.72, + "end": 116.0, + "confidence": 0.809 + }, + { + "text": "dépense", + "start": 116.0, + "end": 116.38, + "confidence": 0.766 + }, + { + "text": "n'était", + "start": 116.38, + "end": 116.62, + "confidence": 0.952 + }, + { + "text": "pas", + "start": 116.62, + "end": 117.02, + 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"end": 134.14, + "confidence": 0.964 + }, + { + "text": "téléphone", + "start": 134.14, + "end": 134.44, + "confidence": 0.977 + }, + { + "text": "pendant", + "start": 134.44, + "end": 134.8, + "confidence": 0.92 + }, + { + "text": "une", + "start": 134.8, + "end": 135.1, + "confidence": 0.838 + } + ] + }, + { + "id": 38, + "seek": 10970, + "start": 135.1, + "end": 136.84, + "text": " heure chaque soir pour discuter avec un copain.", + "tokens": [ + 30027, + 18920, + 27105, + 2016, + 2983, + 20314, + 4163, + 517, + 2971, + 491, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.394765736144266, + "compression_ratio": 1.7249190938511327, + "no_speech_prob": 9.048193533089943e-06, + "confidence": 0.922, + "words": [ + { + "text": "heure", + "start": 135.1, + "end": 135.36, + "confidence": 0.701 + }, + { + "text": "chaque", + "start": 135.36, + "end": 135.52, + "confidence": 0.957 + }, + { + "text": "soir", + "start": 135.52, + "end": 135.76, + "confidence": 0.997 + }, + { + "text": "pour", + "start": 135.76, + "end": 135.94, + "confidence": 0.983 + }, + { + "text": "discuter", + "start": 135.94, + "end": 136.26, + "confidence": 0.882 + }, + { + "text": "avec", + "start": 136.26, + "end": 136.44, + "confidence": 0.993 + }, + { + "text": "un", + "start": 136.44, + "end": 136.6, + "confidence": 0.976 + }, + { + "text": "copain.", + "start": 136.6, + "end": 136.84, + "confidence": 0.948 + } + ] + }, + { + "id": 39, + "seek": 13702, + "start": 137.26, + "end": 141.8, + "text": " Mais ça ne ressemble pas à ce qu'on peut ressentir à voir même mome aujourd'hui", + "tokens": [ + 6313, + 2788, + 408, + 725, + 37227, + 1736, + 1531, + 1769, + 421, + 6, + 266, + 5977, + 24689, + 317, + 347, + 1531, + 10695, + 5698, + 275, + 423, + 14023, + 6, + 10556 + ], + "temperature": 0.0, + "avg_logprob": -0.5734858703613281, + "compression_ratio": 1.5562700964630225, + "no_speech_prob": 3.1260256037057843e-06, + "confidence": 0.716, + "words": [ + { + "text": "Mais", + "start": 137.26, 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lâcher à l'éantrénée, ça m'a eu immédiate.", + "tokens": [ + 1279, + 4212, + 368, + 287, + 6, + 686, + 15970, + 271, + 368, + 48835, + 6759, + 1531, + 287, + 6, + 526, + 394, + 81, + 3516, + 3856, + 11, + 2788, + 275, + 6, + 64, + 2228, + 3397, + 526, + 4504, + 473, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.5734858703613281, + "compression_ratio": 1.5562700964630225, + "no_speech_prob": 3.1260256037057843e-06, + "confidence": 0.401, + "words": [ + { + "text": "extère", + "start": 145.94, + "end": 146.38, + "confidence": 0.357 + }, + { + "text": "de", + "start": 146.38, + "end": 146.46, + "confidence": 0.253 + }, + { + "text": "l'intempis", + "start": 146.46, + "end": 146.7, + "confidence": 0.153 + }, + { + "text": "de", + "start": 146.7, + "end": 146.9, + "confidence": 0.858 + }, + { + "text": "lâcher", + "start": 146.9, + "end": 147.32, + "confidence": 0.824 + }, + { + "text": "à", + "start": 147.32, + "end": 147.44, + "confidence": 0.494 + }, + { + "text": "l'éantrénée,", + 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"je", + "start": 149.3, + "end": 149.34, + "confidence": 0.425 + }, + { + "text": "dis", + "start": 149.34, + "end": 149.42, + "confidence": 0.316 + }, + { + "text": "ça", + "start": 149.42, + "end": 149.62, + "confidence": 0.953 + }, + { + "text": "pour", + "start": 149.62, + "end": 149.72, + "confidence": 0.971 + }, + { + "text": "le", + "start": 149.72, + "end": 149.82, + "confidence": 0.993 + }, + { + "text": "mome,", + "start": 149.82, + "end": 150.24, + "confidence": 0.575 + }, + { + "text": "mais", + "start": 150.24, + "end": 150.44, + "confidence": 0.713 + }, + { + "text": "évidemment,", + "start": 150.44, + "end": 151.1, + "confidence": 0.775 + }, + { + "text": "va", + "start": 151.1, + "end": 151.28, + "confidence": 0.381 + }, + { + "text": "là", + "start": 151.28, + "end": 151.42, + "confidence": 0.633 + }, + { + "text": "pour", + "start": 151.42, + "end": 151.62, + "confidence": 0.398 + }, + { + "text": "nos", + "start": 151.62, + "end": 151.7, + "confidence": 0.807 + }, + { + "text": "aussi.", + "start": 151.7, + "end": 152.02, + "confidence": 0.145 + } + ] + }, + { + "id": 43, + "seek": 13702, + "start": 152.66, + "end": 154.4, + "text": " Donc, rapport immédiate d'accord.", + "tokens": [ + 7477, + 11, + 18018, + 3397, + 526, + 4504, + 473, + 274, + 6, + 19947, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.5734858703613281, + "compression_ratio": 1.5562700964630225, + "no_speech_prob": 3.1260256037057843e-06, + "confidence": 0.851, + "words": [ + { + "text": "Donc,", + "start": 152.66, + "end": 153.0, + "confidence": 0.985 + }, + { + "text": "rapport", + "start": 153.0, + "end": 153.42, + "confidence": 0.977 + }, + { + "text": "immédiate", + "start": 153.42, + "end": 154.26, + "confidence": 0.825 + }, + { + "text": "d'accord.", + "start": 154.26, + "end": 154.4, + "confidence": 0.806 + } + ] + }, + { + "id": 44, + "seek": 13702, + "start": 154.4, + "end": 157.95, + "text": " Mais pourquoi, à ton impression qu'on en sortira jamais?", + "tokens": [ 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"ス", + "start": 20.16, + "end": 20.22, + "confidence": 0.982 + }, + { + "text": "上", + "start": 20.22, + "end": 20.4, + "confidence": 0.236 + }, + { + "text": "では", + "start": 20.4, + "end": 20.74, + "confidence": 0.763 + } + ] + }, + { + "id": 3, + "seek": 2088, + "start": 20.9, + "end": 27.0, + "text": "サイトとして認識され パブリコンアイコンはサイトボトフのものが 正しく表示されます", + "tokens": [ + 50364, + 23607, + 8040, + 7588, + 3193, + 8822, + 22041, + 43143, + 6722, + 4132, + 15096, + 239, + 28889, + 12376, + 18066, + 4824, + 12817, + 8040, + 18066, + 4824, + 3065, + 23607, + 8040, + 7588, + 37626, + 7588, + 17320, + 2972, + 44726, + 5142, + 220, + 15789, + 26568, + 40053, + 6722, + 4132, + 5368, + 50684 + ], + "temperature": 0.0, + "avg_logprob": -0.35092457005235017, + "compression_ratio": 1.6926406926406927, + "no_speech_prob": 0.06554599106311798, + "confidence": 0.389, + "words": [ + { + "text": "サ", + "start": 20.9, + "end": 21.26, + "confidence": 0.002 + }, + { + "text": "イ", + "start": 21.26, + "end": 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"start": 34.04, + "end": 40.36, + "text": "こちらいたいです ものではありません パブリコンはサブテレクトリーごとに設定した", + "tokens": [ + 51024, + 34395, + 17679, + 1764, + 4767, + 32505, + 2972, + 16719, + 14498, + 30250, + 15096, + 239, + 28889, + 12376, + 18066, + 4824, + 3065, + 23607, + 28889, + 22985, + 16680, + 10825, + 7588, + 12376, + 3384, + 9991, + 3193, + 4108, + 39035, + 12088, + 8533, + 51388 + ], + "temperature": 0.0, + "avg_logprob": -0.35092457005235017, + "compression_ratio": 1.6926406926406927, + "no_speech_prob": 0.06554599106311798, + "confidence": 0.364, + "words": [ + { + "text": "こちら", + "start": 34.04, + "end": 34.54, + "confidence": 0.408 + }, + { + "text": "いた", + "start": 34.54, + "end": 34.82, + "confidence": 0.255 + }, + { + "text": "い", + "start": 34.82, + "end": 34.98, + "confidence": 0.11 + }, + { + "text": "です", + "start": 34.98, + "end": 35.04, + "confidence": 0.021 + }, + { + "text": " も", + "start": 35.04, + "end": 35.18, + "confidence": 0.009 + }, + { + "text": "の", + "start": 35.18, 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"jw": 0.00018999911844730377, + "su": 3.0877136403262284e-09 + } +} \ No newline at end of file diff --git a/tests/expected/tiny_auto/accurate_jp_japanese.mp3.words.json b/tests/expected/tiny_auto/accurate_jp_japanese.mp3.words.json new file mode 100644 index 0000000000000000000000000000000000000000..76823c4aa18dc37660ed459b7cff3811894956d9 --- /dev/null +++ b/tests/expected/tiny_auto/accurate_jp_japanese.mp3.words.json @@ -0,0 +1,1665 @@ +{ + "text": "いきます ニュースタブでのサイトメイション機が 実際と違う検に関するご質問いただいております同じ度メインでデレクトリーごとに 別再度として管理上をしているサイトバリマスのサプテレクトリーごとにわけたサイトは それぞれ パブリシャーセンターに登録していくぐるニュース上ではサイトとして認識され パブリコンアイコンはサイトボトフのものが 正しく表示されますしかし ルグル検査結果のニュースタブでは パブリコンサイトメイショー機ともに 正しくない医療時にいいなりますこちらいたいです ものではありません パブリコンはサブテレクトリーごとに設定した", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.08, + "end": 6.62, + "text": "いきます ニュースタブでのサイトメイション機が 実際と違う検に関するご質問いただいております", + "tokens": [ + 50364, + 47348, + 15096, + 233, + 26167, + 3384, + 9550, + 12144, + 28889, + 2474, + 2972, + 23607, + 8040, + 7588, + 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Эскому зарегиан! Боже улыл! Эскому зарегиан!", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.44, + "end": 1.88, + "text": " Боже улыл!", + "tokens": [ + 50364, + 5697, + 9292, + 1595, + 30975, + 693, + 0, + 50464 + ], + "temperature": 0.0, + "avg_logprob": -0.9444295983565482, + "compression_ratio": 0.8166666666666667, + "no_speech_prob": 0.04268376901745796, + "confidence": 0.317, + "words": [ + { + "text": "Боже", + "start": 0.44, + "end": 0.86, + "confidence": 0.422 + }, + { + "text": "улыл!", + "start": 0.86, + "end": 1.88, + "confidence": 0.261 + } + ] + }, + { + "id": 1, + "seek": 0, + "start": 1.88, + "end": 3.14, + "text": " Эскому зарегиан!", + "tokens": [ + 50464, + 5381, + 4218, + 4161, + 17821, + 4953, + 435, + 1416, + 0, + 50564 + ], + "temperature": 0.0, + "avg_logprob": -0.9444295983565482, + "compression_ratio": 0.8166666666666667, + "no_speech_prob": 0.04268376901745796, + "confidence": 0.396, + "words": [ + { + "text": "Эскому", + "start": 1.88, + "end": 2.3, + "confidence": 0.287 + 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0000000000000000000000000000000000000000..026b0e870b9b6a0f872bacea414fc23f025575d0 --- /dev/null +++ b/tests/expected/tiny_auto/jp_japanese.mp3.words.json @@ -0,0 +1,1518 @@ +{ + "text": "いきます 入室タブでの最図免証記が実際と違う県に関するご質問いただいております同じ度面でデレクトリーごとに 別再度として管理上をしている際と針ます サプテレクトリーごとにわけたサイトはそれぞれ パブリシャーセンターに登録していくグルニュース上では 別再度として認識され パンコン愛行は最図ごと物物は正しく表示されますしかし グルニュースタブでは バブコン最図免証記ともに正しくない以上 時にいいなります こちらいたしても ではありませんパブコンはサプテレクトリーごとに 設定した", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.08, + "end": 6.62, + "text": "いきます 入室タブでの最図免証記が実際と違う県に関するご質問いただいております", + "tokens": [ + 50364, + 47348, + 220, + 14028, + 2415, + 97, + 12144, + 28889, + 2474, + 2972, + 8661, + 3919, + 111, + 2347, + 235, + 5396, + 120, + 16958, + 5142, + 33197, + 34837, + 3193, + 49806, + 2862, + 234, + 4108, + 5196, + 95, + 22570, + 9991, + 43450, + 11361, + 32418, + 18549, + 6117, + 19420, + 50712 + ], + "temperature": 0.0, + "avg_logprob": -0.568543427909901, + "compression_ratio": 1.582191780821918, + "no_speech_prob": 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+ { + "text": "いただ", + "start": 5.6, + "end": 5.92, + "confidence": 0.923 + }, + { + "text": "いて", + "start": 5.92, + "end": 6.16, + "confidence": 0.982 + }, + { + "text": "お", + "start": 6.16, + "end": 6.26, + "confidence": 0.791 + }, + { + "text": "ります", + "start": 6.26, + "end": 6.62, + "confidence": 0.976 + } + ] + }, + { + "id": 1, + "seek": 0, + "start": 6.92, + "end": 12.9, + "text": "同じ度面でデレクトリーごとに 別再度として管理上をしている際と針", + "tokens": [ + 50712, + 13089, + 9257, + 13127, + 8833, + 2474, + 31327, + 16680, + 10825, + 7588, + 12376, + 3384, + 9991, + 3193, + 4108, + 220, + 16158, + 8623, + 13127, + 3193, + 8822, + 23131, + 13876, + 5708, + 5998, + 8822, + 22979, + 34837, + 3193, + 5873, + 251, + 51010 + ], + "temperature": 0.0, + "avg_logprob": -0.568543427909901, + "compression_ratio": 1.582191780821918, + "no_speech_prob": 0.18977835774421692, + "confidence": 0.524, + "words": [ + { + "text": "同", + "start": 6.92, + "end": 7.3, + "confidence": 0.834 + }, + { + "text": "じ", + "start": 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"text": "正", + "start": 31.66, + "end": 31.96, + "confidence": 0.482 + }, + { + "text": "しく", + "start": 31.96, + "end": 32.18, + "confidence": 0.999 + }, + { + "text": "ない", + "start": 32.18, + "end": 32.39, + "confidence": 0.937 + } + ] + }, + { + "id": 5, + "seek": 2726, + "start": 32.39, + "end": 36.34, + "text": "以上 時にいいなります こちらいたしても ではありません", + "tokens": [ + 50620, + 29497, + 220, + 6611, + 4108, + 13806, + 3203, + 19420, + 14384, + 28567, + 17679, + 8822, + 4801, + 220, + 16719, + 14498, + 30250, + 50838 + ], + "temperature": 0.0, + "avg_logprob": -0.44633566366659627, + "compression_ratio": 1.375, + "no_speech_prob": 0.35541412234306335, + "confidence": 0.456, + "words": [ + { + "text": "以上", + "start": 32.39, + "end": 32.74, + "confidence": 0.31 + }, + { + "text": " ", + "start": 32.74, + "end": 33.04, + "confidence": 0.126 + }, + { + "text": "時", + "start": 33.04, + "end": 33.1, + "confidence": 0.35 + }, + { + "text": "に", + "start": 33.1, + "end": 33.12, + "confidence": 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6, + "seek": 2726, + "start": 36.42, + "end": 40.4, + "text": "パブコンはサプテレクトリーごとに 設定した", + "tokens": [ + 50838, + 23268, + 28889, + 18066, + 4824, + 3065, + 23607, + 20953, + 22985, + 16680, + 10825, + 7588, + 12376, + 3384, + 9991, + 3193, + 4108, + 220, + 39035, + 12088, + 8533, + 51042 + ], + "temperature": 0.0, + "avg_logprob": -0.44633566366659627, + "compression_ratio": 1.375, + "no_speech_prob": 0.35541412234306335, + "confidence": 0.848, + "words": [ + { + "text": "パ", + "start": 36.42, + "end": 36.92, + "confidence": 0.477 + }, + { + "text": "ブ", + "start": 36.92, + "end": 37.04, + "confidence": 0.649 + }, + { + "text": "コ", + "start": 37.04, + "end": 37.2, + "confidence": 0.678 + }, + { + "text": "ン", + "start": 37.2, + "end": 37.72, + "confidence": 0.994 + }, + { + "text": "は", + "start": 37.72, + "end": 37.74, + "confidence": 0.975 + }, + { + "text": "サ", + "start": 37.74, + "end": 38.22, + "confidence": 0.667 + }, + { + "text": "プ", + "start": 38.22, + "end": 38.32, + 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"した", + "start": 40.02, + "end": 40.4, + "confidence": 0.873 + } + ] + } + ], + "language": "Japanese" +} \ No newline at end of file diff --git a/tests/expected/tiny_auto/laugh1.mp3.words.json b/tests/expected/tiny_auto/laugh1.mp3.words.json new file mode 100644 index 0000000000000000000000000000000000000000..50b70f39baaa87556c0f3cf8336a32055e01789f --- /dev/null +++ b/tests/expected/tiny_auto/laugh1.mp3.words.json @@ -0,0 +1,163 @@ +{ + "text": " You can't do it, man.", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.0, + "end": 1.44, + "text": " You can't do it, man.", + "tokens": [ + 50364, + 509, + 393, + 380, + 360, + 309, + 11, + 587, + 13, + 50464 + ], + "temperature": 0.0, + "avg_logprob": -1.4257353869351475, + "compression_ratio": 0.7241379310344828, + "no_speech_prob": 0.4177960157394409, + "confidence": 0.189, + "words": [ + { + "text": "You", + "start": 0.0, + "end": 0.56, + "confidence": 0.081 + }, + { + "text": "can't", + "start": 0.56, + "end": 0.82, + 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Ce qui fait la force du smartphone, c'est pas seulement la cumulation des fonctions, mais la manière dans quelques interagues entraîne. Et il est d'ailleurs, c'est la photo c'est hyper convaincant. Alors évidemment, il faudrait ajouter les interfaces les grand-attachilles à été beaucoup très souvent mentionnées. Mais bon, il faudrait que les profites aussi de 20 ans pendant l'été, les ordinateurs nous ont appris à piquer sur des icônes, sauf que, alors le smartphone ajoute le toucher, qui rend le contact plus direct, plus sensible. Et puis, évidemment, il faudrait parler aussi des applications qui permettent de contourner le côté tout flu de la navigation web pour aller directement en but. Bref, tout ça, ce sont les conditions qui permettent de créer cette objet, en Nicolas, dit qu'il est très symbolablement inédit dans l'histoire de l'humanité. Mais ça s'assoulait d'une autre interrogation. Est-ce que le fait que cette objet soit inédit un d'huits que notre rapport a lui est aussi un rapport inédit ? Est-ce que le rapport qu'on a au sein de foi n'est comparable à celui qu'on entretenait à d'autres objectes techniques comme la voiture ou le téléphone ? Il n'y a pas d'équivalent. On s'est espèrent de nous voter dans la relation à l'objet. C'est facilement éterricion. Parce que la passion de l'utilisateur et ses affices a dépendance, cette objet d'un lieu en fait, une espèce de relation de médiation avec le monde qui rendent encore avec la maille de celles formes de rogeur. Donc, à objets inédits, rapport inédits. Et, ce rapport, si j'en prends Nicolas, frère caractérisée par un mélange de dépendance et de rogeur. Bon, en vrai, il faudrait remonter très, très filmant tout l'histoire des objectes techniques et de leur infertion dans nos vieux pour déterminer si ce rapport est totalement inédit. Mais j'ai l'impression comme ça que Nicolas se trompe pas vraiment. Pour autant, je sache. Il y a eu plein de discussions autour de la voiture ou même du téléphone. Mais, la dépense n'était pas du même mort, donc le rejet n'en plus n'était pas du même mort. On peut adorer sa bagnure. On a par besoin pour plein de choses. Et là, le soir, quand on va se coucher, on la laisse. On la pade en la main quand on est colis, qu'on n'a même pas au chiot. On pouvait être émervé par son mome qui occupeait la ligne de téléphone pendant une heure chaque soir pour discuter avec un copain. Mais ça ne ressemble pas à ce qu'on peut ressentir à voir même mome aujourd'hui. Continuellement avec son smartphone dans la main, comme c'était une sorte de estimateur extère de tomber de lâcher à l'éantrénée, ça m'a eu immédiate. Bon, je dis ça pour le mome, mais évidemment, va là, bon aussi. Donc, rapport immédiate d'accord. Mais pourquoi, à ton impression qu'on en sortira, j'amé? Et puis, il faut en remettre la faute sur les gens qui ont créé cette critique merveilleux et diabolique et diabolique par que merveilleux. Les économistes parlent de dépendance du santé. Ces vidéos, en fait, on est un santé qui a été étabis, un soit mon termine, en marchand dessus, soit des finissants débordes, des finissants, une signalétique.", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.42, + "end": 3.66, + "text": " C'est évidence que dit Nicolas, mais je me l'étais jamais formulé comme ça.", + "tokens": [ + 50364, + 383, + 6, + 377, + 20090, + 2778, + 631, + 6176, + 38268, + 11, + 2420, + 1506, + 385, + 287, + 6, + 22824, + 14540, + 49990, + 526, + 5173, + 2788, + 13, + 50545 + ], + "temperature": 0.0, + "avg_logprob": -0.5387768369732481, + "compression_ratio": 1.6505681818181819, + "no_speech_prob": 0.14262977242469788, + "confidence": 0.709, + "words": [ + { + "text": "C'est", + "start": 0.42, + "end": 0.68, + "confidence": 0.85 + }, + { + "text": "évidence", + "start": 0.68, + "end": 0.94, + "confidence": 0.368 + }, + { + "text": "que", + "start": 0.94, + "end": 1.08, + "confidence": 0.882 + }, + { + "text": "dit", + "start": 1.08, + "end": 1.2, + 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"pas", + "start": 6.2, + "end": 6.26, + "confidence": 0.983 + }, + { + "text": "seulement", + "start": 6.26, + "end": 6.6, + "confidence": 0.993 + }, + { + "text": "la", + "start": 6.6, + "end": 6.8, + "confidence": 0.636 + }, + { + "text": "cumulation", + "start": 6.8, + "end": 7.34, + "confidence": 0.691 + }, + { + "text": "des", + "start": 7.34, + "end": 7.56, + "confidence": 0.793 + }, + { + "text": "fonctions,", + "start": 7.56, + "end": 8.14, + "confidence": 0.832 + }, + { + "text": "mais", + "start": 8.38, + "end": 8.5, + "confidence": 0.669 + }, + { + "text": "la", + "start": 8.5, + "end": 8.62, + "confidence": 0.718 + }, + { + "text": "manière", + "start": 8.62, + "end": 8.9, + "confidence": 0.498 + } + ] + }, + { + "id": 2, + "seek": 0, + "start": 8.9, + "end": 10.98, + "text": " dans quelques interagues entraîne.", + "tokens": [ + 50806, + 2680, + 16597, + 728, + 559, + 1247, + 22284, + 24741, + 13, + 50906 + ], + "temperature": 0.0, + "avg_logprob": -0.5387768369732481, + "compression_ratio": 1.6505681818181819, + "no_speech_prob": 0.14262977242469788, + "confidence": 0.303, + "words": [ + { + "text": "dans", + "start": 8.9, + "end": 9.06, + "confidence": 0.283 + }, + { + "text": "quelques", + "start": 9.06, + "end": 9.28, + "confidence": 0.281 + }, + { + "text": "interagues", + "start": 9.28, + "end": 10.38, + "confidence": 0.245 + }, + { + "text": "entraîne.", + "start": 10.38, + "end": 10.98, + "confidence": 0.446 + } + ] + }, + { + "id": 3, + "seek": 0, + "start": 11.0, + "end": 12.96, + "text": " Et il est d'ailleurs, c'est la photo c'est hyper convaincant.", + "tokens": [ + 50906, + 3790, + 1930, + 871, + 274, + 6, + 19400, + 11, + 269, + 6, + 377, + 635, + 5052, + 269, + 6, + 377, + 9848, + 3754, + 491, + 66, + 394, + 13, + 51006 + ], + "temperature": 0.0, + "avg_logprob": -0.5387768369732481, + "compression_ratio": 1.6505681818181819, + "no_speech_prob": 0.14262977242469788, + "confidence": 0.63, + "words": [ + { + "text": "Et", + "start": 11.0, + "end": 11.12, + "confidence": 0.362 + }, + { + "text": "il", + "start": 11.12, + "end": 11.28, + "confidence": 0.144 + }, + { + "text": "est", + "start": 11.28, + "end": 11.38, + "confidence": 0.24 + }, + { + "text": "d'ailleurs,", + "start": 11.38, + "end": 11.6, + "confidence": 0.904 + }, + { + "text": "c'est", + "start": 11.7, + "end": 11.78, + "confidence": 0.886 + }, + { + "text": "la", + "start": 11.78, + "end": 11.8, + "confidence": 0.969 + }, + { + "text": "photo", + "start": 11.8, + "end": 12.02, + "confidence": 0.809 + }, + { + "text": "c'est", + "start": 12.02, + "end": 12.26, + "confidence": 0.784 + }, + { + "text": "hyper", + "start": 12.26, + "end": 12.46, + "confidence": 0.938 + }, + { + "text": "convaincant.", + "start": 12.46, + "end": 12.96, + "confidence": 0.509 + } + ] + }, + { + "id": 4, + "seek": 0, + "start": 13.3, + "end": 18.8, + "text": " Alors évidemment, il faudrait ajouter les interfaces les grand-attachilles à été beaucoup très souvent", + "tokens": [ + 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+ "end": 16.5, + "confidence": 0.465 + }, + { + "text": "grand-attachilles", + "start": 16.5, + "end": 17.16, + "confidence": 0.214 + }, + { + "text": "à", + "start": 17.16, + "end": 17.32, + "confidence": 0.408 + }, + { + "text": "été", + "start": 17.32, + "end": 17.72, + "confidence": 0.894 + }, + { + "text": "beaucoup", + "start": 17.72, + "end": 18.28, + "confidence": 0.798 + }, + { + "text": "très", + "start": 18.28, + "end": 18.64, + "confidence": 0.493 + }, + { + "text": "souvent", + "start": 18.64, + "end": 18.8, + "confidence": 0.823 + } + ] + }, + { + "id": 5, + "seek": 0, + "start": 18.8, + "end": 19.84, + "text": " mentionnées.", + "tokens": [ + 51306, + 2152, + 77, + 6836, + 13, + 51356 + ], + "temperature": 0.0, + "avg_logprob": -0.5387768369732481, + "compression_ratio": 1.6505681818181819, + "no_speech_prob": 0.14262977242469788, + "confidence": 0.626, + "words": [ + { + "text": "mentionnées.", + "start": 18.8, + "end": 19.84, + "confidence": 0.626 + } + ] + }, + { + "id": 6, + "seek": 0, + "start": 20.02, + "end": 23.58, + "text": " Mais bon, il faudrait que les profites aussi de 20 ans pendant l'été, les ordinateurs", + "tokens": [ + 51356, + 6313, + 4428, + 11, + 1930, + 38694, + 8645, + 631, + 1512, + 1740, + 3324, + 6212, + 368, + 945, + 1567, + 17338, + 287, + 6, + 21210, + 11, + 1512, + 4792, + 13923, + 2156, + 51543 + ], + "temperature": 0.0, + "avg_logprob": -0.5387768369732481, + "compression_ratio": 1.6505681818181819, + "no_speech_prob": 0.14262977242469788, + "confidence": 0.658, + "words": [ + { + "text": "Mais", + "start": 20.02, + "end": 20.26, + "confidence": 0.979 + }, + { + "text": "bon,", + "start": 20.26, + "end": 20.46, + "confidence": 0.566 + }, + { + "text": "il", + "start": 20.6, + "end": 20.68, + "confidence": 0.975 + }, + { + "text": "faudrait", + "start": 20.68, + "end": 20.78, + "confidence": 0.773 + }, + { + "text": "que", + "start": 20.78, + "end": 20.92, + "confidence": 0.386 + }, + { + "text": "les", + "start": 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"start": 24.9, + "end": 25.56, + "confidence": 0.599 + }, + { + "text": "sauf", + "start": 25.64, + "end": 25.8, + "confidence": 0.521 + }, + { + "text": "que,", + "start": 25.8, + "end": 26.36, + "confidence": 0.915 + }, + { + "text": "alors", + "start": 26.36, + "end": 26.58, + "confidence": 0.399 + }, + { + "text": "le", + "start": 26.58, + "end": 26.72, + "confidence": 0.824 + }, + { + "text": "smartphone", + "start": 26.72, + "end": 27.0, + "confidence": 0.977 + }, + { + "text": "ajoute", + "start": 27.0, + "end": 27.5, + "confidence": 0.673 + }, + { + "text": "le", + "start": 27.5, + "end": 27.62, + "confidence": 0.554 + }, + { + "text": "toucher,", + "start": 27.62, + "end": 28.07, + "confidence": 0.631 + } + ] + }, + { + "id": 8, + "seek": 2804, + "start": 28.07, + "end": 30.6, + "text": " qui rend le contact plus direct, plus sensible.", + "tokens": [ + 50364, + 1956, + 6125, + 476, + 3385, + 1804, + 2047, + 11, + 1804, + 25380, + 13, + 50496 + ], + "temperature": 0.0, + 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le côté", + "tokens": [ + 50496, + 3790, + 9093, + 11, + 24724, + 11, + 1930, + 38694, + 8645, + 16421, + 6212, + 730, + 5821, + 1956, + 21540, + 317, + 368, + 21234, + 1193, + 476, + 18437, + 50698 + ], + "temperature": 0.0, + "avg_logprob": -0.4260108065442974, + "compression_ratio": 1.7156549520766773, + "no_speech_prob": 0.1274678260087967, + "confidence": 0.775, + "words": [ + { + "text": "Et", + "start": 31.1, + "end": 31.24, + "confidence": 0.949 + }, + { + "text": "puis,", + "start": 31.24, + "end": 31.36, + "confidence": 0.725 + }, + { + "text": "évidemment,", + "start": 31.42, + "end": 31.62, + "confidence": 0.211 + }, + { + "text": "il", + "start": 31.7, + "end": 31.76, + "confidence": 0.959 + }, + { + "text": "faudrait", + "start": 31.76, + "end": 31.94, + "confidence": 0.994 + }, + { + "text": "parler", + "start": 31.94, + "end": 32.14, + "confidence": 0.847 + }, + { + "text": "aussi", + "start": 32.14, + "end": 32.36, + "confidence": 0.924 + }, + { + "text": "des", + 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37.86, + "confidence": 0.768 + } + ] + }, + { + "id": 11, + "seek": 2804, + "start": 38.78, + "end": 43.13, + "text": " Bref, tout ça, ce sont les conditions qui permettent de créer cette objet, en Nicolas,", + "tokens": [ + 50860, + 49957, + 11, + 3486, + 2788, + 11, + 1769, + 4900, + 1512, + 4487, + 1956, + 21540, + 317, + 368, + 32062, + 5550, + 14964, + 11, + 465, + 38268, + 11, + 51121 + ], + "temperature": 0.0, + "avg_logprob": -0.4260108065442974, + "compression_ratio": 1.7156549520766773, + "no_speech_prob": 0.1274678260087967, + "confidence": 0.738, + "words": [ + { + "text": "Bref,", + "start": 38.78, + "end": 38.8, + "confidence": 0.972 + }, + { + "text": "tout", + "start": 38.84, + "end": 39.04, + "confidence": 0.816 + }, + { + "text": "ça,", + "start": 39.04, + "end": 39.46, + "confidence": 0.984 + }, + { + "text": "ce", + "start": 39.54, + "end": 39.76, + "confidence": 0.905 + }, + { + "text": "sont", + "start": 39.76, + "end": 39.96, + "confidence": 0.981 + }, + { + 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45.74, + "end": 46.02, + "confidence": 0.825 + }, + { + "text": "de", + "start": 46.02, + "end": 46.14, + "confidence": 0.984 + }, + { + "text": "l'humanité.", + "start": 46.14, + "end": 46.58, + "confidence": 0.99 + } + ] + }, + { + "id": 13, + "seek": 2804, + "start": 47.06, + "end": 48.76, + "text": " Mais ça s'assoulait d'une autre interrogation.", + "tokens": [ + 51290, + 6313, + 2788, + 262, + 6, + 640, + 263, + 35235, + 274, + 6, + 2613, + 15081, + 24871, + 399, + 13, + 51402 + ], + "temperature": 0.0, + "avg_logprob": -0.4260108065442974, + "compression_ratio": 1.7156549520766773, + "no_speech_prob": 0.1274678260087967, + "confidence": 0.718, + "words": [ + { + "text": "Mais", + "start": 47.06, + "end": 47.24, + "confidence": 0.928 + }, + { + "text": "ça", + "start": 47.24, + "end": 47.48, + "confidence": 0.75 + }, + { + "text": "s'assoulait", + "start": 47.48, + "end": 47.84, + "confidence": 0.616 + }, + { + "text": "d'une", + "start": 47.84, + "end": 48.08, + "confidence": 0.675 + }, + { + "text": "autre", + "start": 48.08, + "end": 48.18, + "confidence": 0.964 + }, + { + "text": "interrogation.", + "start": 48.18, + "end": 48.76, + "confidence": 0.855 + } + ] + }, + { + "id": 14, + "seek": 2804, + "start": 49.42, + "end": 54.93, + "text": " Est-ce que le fait que cette objet soit inédit un d'huits que notre rapport a lui est aussi un rapport", + "tokens": [ + 51402, + 4410, + 12, + 384, + 631, + 476, + 3887, + 631, + 5550, + 14964, + 12703, + 294, + 7811, + 270, + 517, + 274, + 6, + 12086, + 1208, + 631, + 10349, + 18018, + 257, + 8783, + 871, + 6212, + 517, + 18018, + 51710 + ], + "temperature": 0.0, + "avg_logprob": -0.4260108065442974, + "compression_ratio": 1.7156549520766773, + "no_speech_prob": 0.1274678260087967, + "confidence": 0.704, + "words": [ + { + "text": "Est-ce", + "start": 49.42, + "end": 49.7, + "confidence": 0.919 + }, + { + "text": "que", + "start": 49.7, + "end": 49.74, + "confidence": 0.989 + }, + { + "text": "le", + "start": 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53.24, + "end": 53.5, + "confidence": 0.572 + }, + { + "text": "lui", + "start": 53.5, + "end": 53.7, + "confidence": 0.698 + }, + { + "text": "est", + "start": 53.7, + "end": 54.04, + "confidence": 0.88 + }, + { + "text": "aussi", + "start": 54.04, + "end": 54.52, + "confidence": 0.814 + }, + { + "text": "un", + "start": 54.52, + "end": 54.7, + "confidence": 0.48 + }, + { + "text": "rapport", + "start": 54.7, + "end": 54.93, + "confidence": 0.951 + } + ] + }, + { + "id": 15, + "seek": 2804, + "start": 54.93, + "end": 55.88, + "text": " inédit ?", + "tokens": [ + 51710, + 294, + 7811, + 270, + 2506, + 51760 + ], + "temperature": 0.0, + "avg_logprob": -0.4260108065442974, + "compression_ratio": 1.7156549520766773, + "no_speech_prob": 0.1274678260087967, + "confidence": 0.86, + "words": [ + { + "text": "inédit ?", + "start": 54.93, + "end": 55.88, + "confidence": 0.86 + } + ] + }, + { + "id": 16, + "seek": 5596, + "start": 55.96, + "end": 59.36, + "text": " Est-ce que le rapport qu'on a au sein de foi n'est comparable à celui qu'on entretenait", + "tokens": [ + 50364, + 4410, + 12, + 384, + 631, + 476, + 18018, + 421, + 6, + 266, + 257, + 1609, + 6195, + 368, + 6901, + 297, + 6, + 377, + 25323, + 1531, + 22829, + 421, + 6, + 266, + 3962, + 1147, + 1001, + 50530 + ], + "temperature": 0.0, + "avg_logprob": -0.6289185115269252, + "compression_ratio": 1.5749128919860627, + "no_speech_prob": 0.21948665380477905, + "confidence": 0.62, + "words": [ + { + "text": "Est-ce", + "start": 55.96, + "end": 56.38, + "confidence": 0.55 + }, + { + "text": "que", + "start": 56.38, + "end": 56.44, + "confidence": 0.892 + }, + { + "text": "le", + "start": 56.44, + "end": 56.58, + "confidence": 0.982 + }, + { + "text": "rapport", + "start": 56.58, + "end": 56.9, + "confidence": 0.999 + }, + { + "text": "qu'on", + "start": 56.9, + "end": 57.14, + "confidence": 0.904 + }, + { + "text": "a", + "start": 57.14, + "end": 57.2, + "confidence": 0.959 + }, + { + "text": "au", + "start": 57.2, + "end": 57.28, + "confidence": 0.272 + }, + { + "text": "sein", + "start": 57.28, + "end": 57.42, + "confidence": 0.17 + }, + { + "text": "de", + "start": 57.42, + "end": 57.56, + "confidence": 0.23 + }, + { + "text": "foi", + "start": 57.56, + "end": 57.58, + "confidence": 0.121 + }, + { + "text": "n'est", + "start": 57.58, + "end": 57.78, + "confidence": 0.79 + }, + { + "text": "comparable", + "start": 57.78, + "end": 58.28, + "confidence": 0.547 + }, + { + "text": "à", + "start": 58.28, + "end": 58.48, + "confidence": 0.934 + }, + { + "text": "celui", + "start": 58.48, + "end": 58.7, + "confidence": 0.851 + }, + { + "text": "qu'on", + "start": 58.7, + "end": 58.94, + "confidence": 0.926 + }, + { + "text": "entretenait", + "start": 58.94, + "end": 59.36, + "confidence": 0.56 + } + ] + }, + { + "id": 17, + "seek": 5596, + "start": 59.36, + "end": 63.14, + "text": " à d'autres objectes techniques comme la voiture ou le téléphone ?", + "tokens": [ + 50530, + 1531, + 274, + 6, + 16752, + 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"confidence": 0.912 + }, + { + "text": "téléphone ?", + "start": 62.68, + "end": 63.14, + "confidence": 0.983 + } + ] + }, + { + "id": 18, + "seek": 5596, + "start": 65.4, + "end": 66.16, + "text": " Il n'y a pas d'équivalent.", + "tokens": [ + 50714, + 4416, + 297, + 6, + 88, + 257, + 1736, + 274, + 6, + 20183, + 3576, + 317, + 13, + 50872 + ], + "temperature": 0.0, + "avg_logprob": -0.6289185115269252, + "compression_ratio": 1.5749128919860627, + "no_speech_prob": 0.21948665380477905, + "confidence": 0.881, + "words": [ + { + "text": "Il", + "start": 65.4, + "end": 65.5, + "confidence": 0.901 + }, + { + "text": "n'y", + "start": 65.5, + "end": 65.54, + "confidence": 0.859 + }, + { + "text": "a", + "start": 65.54, + "end": 65.56, + "confidence": 0.962 + }, + { + "text": "pas", + "start": 65.56, + "end": 65.68, + "confidence": 0.998 + }, + { + "text": "d'équivalent.", + "start": 65.68, + "end": 66.16, + "confidence": 0.853 + } + ] + }, + { + "id": 19, + "seek": 5596, + "start": 66.16, + "end": 69.92, + "text": " On s'est espèrent de nous voter dans la relation à l'objet.", + "tokens": [ + 50872, + 1282, + 262, + 6, + 377, + 7089, + 1462, + 1753, + 368, + 4666, + 21722, + 2680, + 635, + 9721, + 1531, + 287, + 6, + 996, + 7108, + 13, + 51058 + ], + "temperature": 0.0, + "avg_logprob": -0.6289185115269252, + "compression_ratio": 1.5749128919860627, + "no_speech_prob": 0.21948665380477905, + "confidence": 0.501, + "words": [ + { + "text": "On", + "start": 66.16, + "end": 67.08, + "confidence": 0.301 + }, + { + "text": "s'est", + "start": 67.08, + "end": 67.3, + "confidence": 0.561 + }, + { + "text": "espèrent", + "start": 67.3, + "end": 67.62, + "confidence": 0.134 + }, + { + "text": "de", + "start": 67.62, + "end": 67.66, + "confidence": 0.99 + }, + { + "text": "nous", + "start": 67.66, + "end": 67.84, + "confidence": 0.763 + }, + { + "text": "voter", + "start": 67.84, + "end": 68.36, + "confidence": 0.183 + }, + { + "text": "dans", + "start": 68.36, + "end": 68.86, + "confidence": 0.82 + }, + { + "text": "la", + "start": 68.86, + "end": 68.96, + "confidence": 0.614 + }, + { + "text": "relation", + "start": 68.96, + "end": 69.24, + "confidence": 0.949 + }, + { + "text": "à", + "start": 69.24, + "end": 69.42, + "confidence": 0.75 + }, + { + "text": "l'objet.", + "start": 69.42, + "end": 69.92, + "confidence": 0.887 + } + ] + }, + { + "id": 20, + "seek": 5596, + "start": 70.2, + "end": 71.22, + "text": " C'est facilement éterricion.", + "tokens": [ + 51058, + 383, + 6, + 377, + 23670, + 518, + 1136, + 391, + 1341, + 313, + 13, + 51122 + ], + "temperature": 0.0, + "avg_logprob": -0.6289185115269252, + "compression_ratio": 1.5749128919860627, + "no_speech_prob": 0.21948665380477905, + "confidence": 0.443, + "words": [ + { + "text": "C'est", + "start": 70.2, + "end": 70.34, + "confidence": 0.896 + }, + { + "text": "facilement", + "start": 70.34, + "end": 70.7, + "confidence": 0.566 + }, + { + "text": "éterricion.", + "start": 70.7, + "end": 71.22, + "confidence": 0.231 + } + ] + }, + { + "id": 21, + "seek": 5596, + "start": 71.64, + "end": 76.97, + "text": " Parce que la passion de l'utilisateur et ses affices a dépendance, cette objet d'un lieu", + "tokens": [ + 51122, + 20429, + 631, + 635, + 5418, + 368, + 287, + 6, + 20835, + 271, + 15540, + 1030, + 5385, + 2096, + 1473, + 257, + 45768, + 719, + 11, + 5550, + 14964, + 274, + 6, + 409, + 26036, + 51416 + ], + "temperature": 0.0, + "avg_logprob": -0.6289185115269252, + "compression_ratio": 1.5749128919860627, + "no_speech_prob": 0.21948665380477905, + "confidence": 0.457, + "words": [ + { + "text": "Parce", + "start": 71.64, + "end": 71.94, + "confidence": 0.68 + }, + { + "text": "que", + "start": 71.94, + "end": 72.32, + "confidence": 0.566 + }, + { + "text": "la", + "start": 72.32, + "end": 72.56, + "confidence": 0.333 + }, + { + "text": "passion", + "start": 72.56, + "end": 72.9, + "confidence": 0.266 + }, + { + "text": "de", + "start": 72.9, + "end": 73.26, + "confidence": 0.365 + }, + { + "text": "l'utilisateur", + "start": 73.26, + "end": 74.82, + "confidence": 0.5 + }, + { + "text": "et", + "start": 74.82, + "end": 74.92, + "confidence": 0.452 + }, + { + "text": "ses", + "start": 74.92, + "end": 75.04, + "confidence": 0.095 + }, + { + "text": "affices", + "start": 75.04, + "end": 75.24, + "confidence": 0.302 + }, + { + "text": "a", + "start": 75.24, + "end": 75.38, + "confidence": 0.589 + }, + { + "text": "dépendance,", + "start": 75.38, + "end": 76.06, + "confidence": 0.561 + }, + { + "text": "cette", + "start": 76.32, + "end": 76.34, + "confidence": 0.399 + }, + { + "text": "objet", + "start": 76.34, + "end": 76.54, + "confidence": 0.924 + }, + { + "text": "d'un", + "start": 76.54, + "end": 76.92, + "confidence": 0.781 + }, + { + "text": "lieu", + "start": 76.92, + "end": 76.97, + "confidence": 0.305 + } + ] + }, + { + "id": 22, + "seek": 5596, + "start": 76.97, + "end": 82.15, + "text": " en fait, une espèce de relation de médiation avec le monde qui rendent encore avec", + "tokens": [ + 51416, + 465, + 3887, + 11, + 2251, + 7089, + 30236, + 368, + 9721, + 368, + 42436, + 399, + 4163, + 476, + 10431, + 1956, + 6125, + 317, + 10122, + 4163, + 51671 + ], + "temperature": 0.0, + "avg_logprob": -0.6289185115269252, + "compression_ratio": 1.5749128919860627, + "no_speech_prob": 0.21948665380477905, + "confidence": 0.746, + "words": [ + { + "text": "en", + "start": 76.97, + "end": 77.2, + "confidence": 0.77 + }, + { + "text": "fait,", + "start": 77.2, + "end": 77.32, + "confidence": 0.944 + }, + { + "text": "une", + "start": 77.46, + "end": 77.48, + "confidence": 0.699 + }, + { + "text": "espèce", + "start": 77.48, + "end": 77.9, + "confidence": 0.97 + }, + { + "text": "de", + "start": 77.9, + "end": 78.08, + "confidence": 0.993 + }, + { + "text": "relation", + "start": 78.08, + "end": 78.5, + "confidence": 0.827 + }, + { + "text": "de", + "start": 78.5, + "end": 78.94, + "confidence": 0.714 + }, + { + "text": "médiation", + "start": 78.94, + "end": 79.5, + "confidence": 0.88 + }, + { + "text": "avec", + "start": 79.5, + "end": 79.74, + "confidence": 0.968 + }, + { + "text": "le", + "start": 79.74, + "end": 79.94, + "confidence": 0.986 + }, + { + "text": "monde", + "start": 79.94, + "end": 80.44, + "confidence": 0.906 + }, + { + "text": "qui", + "start": 80.44, + "end": 81.14, + "confidence": 0.823 + }, + { + "text": "rendent", + "start": 81.14, + "end": 81.8, + "confidence": 0.586 + }, + { + "text": "encore", + "start": 81.8, + "end": 81.98, + "confidence": 0.198 + }, + { + "text": "avec", + "start": 81.98, + "end": 82.15, + "confidence": 0.491 + } + ] + }, + { + "id": 23, + "seek": 8210, + "start": 82.15, + "end": 83.44, + "text": " la maille de celles formes de rogeur.", + "tokens": [ + 50364, + 635, + 463, + 3409, + 368, + 2815, + 279, + 1254, + 279, + 368, + 744, + 432, + 374, + 13, + 50440 + ], + "temperature": 0.0, + "avg_logprob": -0.45919205838401844, + "compression_ratio": 1.6159169550173011, + 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"id": 27, + "seek": 8210, + "start": 96.3, + "end": 100.48, + "text": " Bon, en vrai, il faudrait remonter très, très filmant tout l'histoire des objectes", + "tokens": [ + 51022, + 7368, + 11, + 465, + 17815, + 11, + 1930, + 38694, + 8645, + 890, + 41806, + 5732, + 11, + 5732, + 2007, + 394, + 3486, + 287, + 6, + 29093, + 730, + 2657, + 279, + 51286 + ], + "temperature": 0.0, + "avg_logprob": -0.45919205838401844, + "compression_ratio": 1.6159169550173011, + "no_speech_prob": 0.2066800743341446, + "confidence": 0.752, + "words": [ + { + "text": "Bon,", + "start": 96.3, + "end": 96.32, + "confidence": 0.601 + }, + { + "text": "en", + "start": 96.36, + "end": 96.58, + "confidence": 0.919 + }, + { + "text": "vrai,", + "start": 96.58, + "end": 96.92, + "confidence": 0.993 + }, + { + "text": "il", + "start": 97.14, + "end": 97.18, + "confidence": 0.987 + }, + { + "text": "faudrait", + "start": 97.18, + "end": 97.56, + "confidence": 0.933 + }, + { + "text": "remonter", + "start": 97.56, + 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j'ai l'impression comme ça que Nicolas se trompe pas vraiment.", + "tokens": [ + 51580, + 6313, + 361, + 6, + 1301, + 287, + 6, + 36107, + 5173, + 2788, + 631, + 38268, + 369, + 504, + 298, + 494, + 1736, + 8322, + 13, + 51738 + ], + "temperature": 0.0, + "avg_logprob": -0.45919205838401844, + "compression_ratio": 1.6159169550173011, + "no_speech_prob": 0.2066800743341446, + "confidence": 0.811, + "words": [ + { + "text": "Mais", + "start": 106.16, + "end": 106.5, + "confidence": 0.723 + }, + { + "text": "j'ai", + "start": 106.5, + "end": 106.92, + "confidence": 0.91 + }, + { + "text": "l'impression", + "start": 106.92, + "end": 107.34, + "confidence": 0.956 + }, + { + "text": "comme", + "start": 107.34, + "end": 107.58, + "confidence": 0.7 + }, + { + "text": "ça", + "start": 107.58, + "end": 107.74, + "confidence": 0.953 + }, + { + "text": "que", + "start": 107.74, + "end": 108.06, + "confidence": 0.941 + }, + { + "text": "Nicolas", + "start": 108.06, + "end": 108.46, + "confidence": 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"sache.", + "start": 110.48, + "end": 110.86, + "confidence": 0.479 + } + ] + }, + { + "id": 32, + "seek": 11098, + "start": 111.04, + "end": 115.0, + "text": " Il y a eu plein de discussions autour de la voiture ou même du téléphone.", + "tokens": [ + 50364, + 4416, + 288, + 257, + 2228, + 21088, + 368, + 11088, + 30249, + 368, + 635, + 38859, + 2820, + 5698, + 1581, + 47159, + 13, + 50568 + ], + "temperature": 0.0, + "avg_logprob": -0.44286312419138135, + "compression_ratio": 1.7050847457627119, + "no_speech_prob": 0.14988036453723907, + "confidence": 0.822, + "words": [ + { + "text": "Il", + "start": 111.04, + "end": 111.2, + "confidence": 0.905 + }, + { + "text": "y", + "start": 111.2, + "end": 111.3, + "confidence": 0.934 + }, + { + "text": "a", + "start": 111.3, + "end": 111.56, + "confidence": 0.894 + }, + { + "text": "eu", + "start": 111.56, + "end": 111.6, + "confidence": 0.839 + }, + { + "text": "plein", + "start": 111.6, + "end": 111.88, + "confidence": 0.774 + }, + { + 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plus n'était pas du même", + "tokens": [ + 50568, + 6313, + 11, + 635, + 27998, + 1288, + 297, + 6, + 9743, + 1736, + 1581, + 5698, + 6599, + 11, + 5926, + 476, + 319, + 7108, + 297, + 6, + 268, + 1804, + 297, + 6, + 9743, + 1736, + 1581, + 5698, + 50790 + ], + "temperature": 0.0, + "avg_logprob": -0.44286312419138135, + "compression_ratio": 1.7050847457627119, + "no_speech_prob": 0.14988036453723907, + "confidence": 0.702, + "words": [ + { + "text": "Mais,", + "start": 115.52, + "end": 115.82, + "confidence": 0.984 + }, + { + "text": "la", + "start": 115.92, + "end": 116.0, + "confidence": 0.961 + }, + { + "text": "dépense", + "start": 116.0, + "end": 116.42, + "confidence": 0.616 + }, + { + "text": "n'était", + "start": 116.42, + "end": 116.82, + "confidence": 0.956 + }, + { + "text": "pas", + "start": 116.82, + "end": 117.04, + "confidence": 0.994 + }, + { + "text": "du", + "start": 117.04, + "end": 117.2, + "confidence": 0.958 + }, + { + "text": "même", + "start": 117.2, + "end": 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"lâcher", + "start": 146.9, + "end": 147.34, + "confidence": 0.751 + }, + { + "text": "à", + "start": 147.34, + "end": 147.46, + "confidence": 0.444 + }, + { + "text": "l'éantrénée,", + "start": 147.46, + "end": 147.9, + "confidence": 0.491 + }, + { + "text": "ça", + "start": 148.0, + "end": 148.02, + "confidence": 0.798 + }, + { + "text": "m'a", + "start": 148.02, + "end": 148.26, + "confidence": 0.529 + }, + { + "text": "eu", + "start": 148.26, + "end": 148.44, + "confidence": 0.136 + }, + { + "text": "immédiate.", + "start": 148.44, + "end": 149.0, + "confidence": 0.502 + } + ] + }, + { + "id": 44, + "seek": 13698, + "start": 149.08, + "end": 151.98, + "text": " Bon, je dis ça pour le mome, mais évidemment, va là, bon aussi.", + "tokens": [ + 50954, + 7368, + 11, + 1506, + 717, + 2788, + 2016, + 476, + 275, + 423, + 11, + 2420, + 24724, + 11, + 2773, + 3684, + 11, + 4428, + 6212, + 13, + 51126 + ], + "temperature": 0.0, + "avg_logprob": -0.5335124224081806, + "compression_ratio": 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"confidence": 0.591 + }, + { + "text": "bon", + "start": 151.6, + "end": 151.68, + "confidence": 0.827 + }, + { + "text": "aussi.", + "start": 151.68, + "end": 151.98, + "confidence": 0.163 + } + ] + }, + { + "id": 45, + "seek": 13698, + "start": 152.64, + "end": 154.64, + "text": " Donc, rapport immédiate d'accord.", + "tokens": [ + 51126, + 7477, + 11, + 18018, + 3397, + 526, + 4504, + 473, + 274, + 6, + 19947, + 13, + 51248 + ], + "temperature": 0.0, + "avg_logprob": -0.5335124224081806, + "compression_ratio": 1.6231454005934718, + "no_speech_prob": 0.10962729901075363, + "confidence": 0.86, + "words": [ + { + "text": "Donc,", + "start": 152.64, + "end": 153.08, + "confidence": 0.982 + }, + { + "text": "rapport", + "start": 153.16, + "end": 153.58, + "confidence": 0.979 + }, + { + "text": "immédiate", + "start": 153.58, + "end": 154.28, + "confidence": 0.839 + }, + { + "text": "d'accord.", + "start": 154.28, + "end": 154.64, + "confidence": 0.815 + } + ] + }, + { + "id": 46, + "seek": 13698, + "start": 155.66, + "end": 158.36, + "text": " Mais pourquoi, à ton impression qu'on en sortira, j'amé?", + "tokens": [ + 51248, + 6313, + 19934, + 11, + 1531, + 2952, + 9995, + 421, + 6, + 266, + 465, + 26906, + 64, + 11, + 361, + 6, + 335, + 526, + 30, + 51440 + ], + "temperature": 0.0, + "avg_logprob": -0.5335124224081806, + "compression_ratio": 1.6231454005934718, + "no_speech_prob": 0.10962729901075363, + "confidence": 0.709, + "words": [ + { + "text": "Mais", + "start": 155.66, + "end": 155.88, + "confidence": 0.984 + }, + { + "text": "pourquoi,", + "start": 155.88, + "end": 156.28, + "confidence": 0.898 + }, + { + "text": "à", + "start": 156.38, + "end": 156.58, + "confidence": 0.838 + }, + { + "text": "ton", + "start": 156.58, + "end": 156.7, + "confidence": 0.952 + }, + { + "text": "impression", + "start": 156.7, + "end": 157.06, + "confidence": 0.939 + }, + { + "text": "qu'on", + "start": 157.06, + "end": 157.28, + "confidence": 0.889 + }, + { + "text": "en", + "start": 157.28, + "end": 157.4, + "confidence": 0.801 + }, + { + "text": "sortira,", + "start": 157.4, + "end": 157.88, + "confidence": 0.577 + }, + { + "text": "j'amé?", + "start": 157.96, + "end": 158.36, + "confidence": 0.463 + } + ] + }, + { + "id": 47, + "seek": 13698, + "start": 159.16, + "end": 163.32, + "text": " Et puis, il faut en remettre la faute sur les gens qui ont créé cette critique merveilleux", + "tokens": [ + 51440, + 3790, + 9093, + 11, + 1930, + 8487, + 465, + 890, + 40681, + 635, + 2050, + 1169, + 1022, + 1512, + 10668, + 1956, + 6592, + 15609, + 526, + 5550, + 25673, + 3551, + 303, + 3409, + 2449, + 51678 + ], + "temperature": 0.0, + "avg_logprob": -0.5335124224081806, + "compression_ratio": 1.6231454005934718, + "no_speech_prob": 0.10962729901075363, + "confidence": 0.715, + "words": [ + { + "text": "Et", + "start": 159.16, + "end": 159.32, + "confidence": 0.83 + }, + { + "text": "puis,", + "start": 159.32, + "end": 159.46, + "confidence": 0.495 + }, + { + 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b/tests/expected/tiny_fr.cpu/smartphone.mp3.words.json new file mode 100644 index 0000000000000000000000000000000000000000..f90643caf0519b49ba0cbc0381cd8d8ced1f218b --- /dev/null +++ b/tests/expected/tiny_fr.cpu/smartphone.mp3.words.json @@ -0,0 +1,5038 @@ +{ + "text": " C'est évidence que dit Nicolas. Mais je me l'étais jamais formulé comme ça. Ce qui fait la force du smartphone, c'est pas seulement la cumulation des fonctions, mais la manière dans quelques interagues entraîne. Et il est d'ailleurs, c'est la photo c'est hyper convaincant. Alors évidemment, il faudrait ajouter les interfaces les grand-attêtes qu'il a été beaucoup très souvent ementionné. Mais bon, il faudrait que les profites aussi de 20 ans pendant l'été, les ordinateurs nous ont appris à piquer sur des icônes. C'est ce que le smartphone ajoute le toucher, qui rend le contact plus direct, plus sensible. Et puis, évidemment, il faudrait parler aussi des applications qui permettent de contourner le côté tout flu de la navigation web pour aller directement en but. Bref, tout ça, ce sont les conditions qui permettent de créer cette objet, en Nicolas, dit qu'il est très fondablement inédit dans l'histoire de l'humanité. Mais ça s'assoulait d'une autre interrogation. Est-ce que le fait que cette objet soit inédit un d'huies que notre rapport a lui est aussi un rapport inédit? Je veux dire, est-ce que le rapport qu'on a au sein de foi n'est comparable à celui qu'on entretenait à d'autres objectes techniques comme la voiture ou le téléphone? Il n'y a pas d'équivalent. On s'est espécie de nous voter dans la relation à l'objet. C'est facilement éterréciant parce qu'on a impression de, comme le 10, les utilisateurs et les efforts, elles aident dépendant de cette objet d'un lieu, en fait, une espèce de relation de médiation avec le monde qui rendent un peu avec la même sédiforme de le jeu. Donc, à objets inédits, rapport inédits. Et, ce rapport, si j'en prends Nicolas, frère caractérisée par un mélange de dépenses et de rojets. Bon, en vrai, il faudrait remonter très très finement toute l'histoire des objectes techniques et de leur infération dans le vie pour déterminer si ce rapport est totalement inédit. Mais j'ai l'impression comme ça que Nicolas se trompe pas vraiment. Pour autant, je sache. Il y a eu plein de discussions autour de la voiture ou même du téléphone. Mais la dépense n'était pas du même mort, donc le rejet n'en plus n'était pas du même mort. On peut adorer sa bagnure, en avoir besoin pour plein de choses. Et là, le soir, quand on va se coucher, on la laisse. On l'a pas dans la main, quand on est collis, quand on n'en mène pas au chiot. On pouvait être émervé par son mome qui occupeait la ligne de téléphone pendant une heure chaque soir pour discuter avec un copain. Mais ça ne ressemble pas à ce qu'on peut ressentir à voir même mome aujourd'hui continuuellement avec son smartphone dans la main, comme c'était une sorte de estimateur extère de l'intempis de lâcher à l'éantrénée, ça m'a eu immédiate. Bon, je dis ça pour le mome, mais évidemment, va là pour nos aussi. Donc, rapport immédiate d'accord. Mais pourquoi, à ton impression qu'on en sortira jamais? Et puis, il faut en remettre la faute sur les gens qui ont créé cette route merveilleux et diabolique, qui a dit à bollique par coeur, merveilleux. Les économistes parlent de dépendance du santé. Ces vidéos, en fait, on est un santé qui a été établie, c'est un soit mon termine, soit définissant des beurs, on définisse un signalétique.", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.42, + "end": 1.38, + "text": " C'est évidence que dit Nicolas.", + "tokens": [ + 383, + 6, + 377, + 20090, + 2778, + 631, + 6176, + 38268, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.566579490710216, + "compression_ratio": 1.605421686746988, + "no_speech_prob": 0.14170263707637787, + "confidence": 0.625, + "words": [ + { + "text": "C'est", + "start": 0.42, + "end": 0.66, + "confidence": 0.849 + }, + { + "text": "évidence", + "start": 0.66, + "end": 0.94, + "confidence": 0.368 + }, + { + "text": "que", + "start": 0.94, + "end": 1.06, + "confidence": 0.883 + }, + { + "text": "dit", + "start": 1.06, + "end": 1.16, + "confidence": 0.344 + }, + { + "text": "Nicolas.", + "start": 1.16, + "end": 1.38, + "confidence": 0.921 + } + ] + }, + { + "id": 1, + "seek": 0, + "start": 1.66, + "end": 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"end": 5.16, + "confidence": 0.936 + }, + { + "text": "smartphone,", + "start": 5.16, + "end": 5.74, + "confidence": 0.909 + }, + { + "text": "c'est", + "start": 5.74, + "end": 6.12, + "confidence": 0.871 + }, + { + "text": "pas", + "start": 6.12, + "end": 6.2, + "confidence": 0.982 + }, + { + "text": "seulement", + "start": 6.2, + "end": 6.52, + "confidence": 0.991 + }, + { + "text": "la", + "start": 6.52, + "end": 6.76, + "confidence": 0.627 + }, + { + "text": "cumulation", + "start": 6.76, + "end": 7.18, + "confidence": 0.679 + }, + { + "text": "des", + "start": 7.18, + "end": 7.54, + "confidence": 0.752 + }, + { + "text": "fonctions,", + "start": 7.54, + "end": 8.1, + "confidence": 0.826 + }, + { + "text": "mais", + "start": 8.1, + "end": 8.42, + "confidence": 0.511 + }, + { + "text": "la", + "start": 8.42, + "end": 8.58, + "confidence": 0.717 + }, + { + "text": "manière", + "start": 8.58, + "end": 8.82, + "confidence": 0.457 + } + ] + }, + { + "id": 3, + "seek": 0, + "start": 8.9, + "end": 10.84, + "text": " dans quelques interagues entraîne.", + "tokens": [ + 2680, + 16597, + 728, + 559, + 1247, + 22284, + 24741, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.566579490710216, + "compression_ratio": 1.605421686746988, + "no_speech_prob": 0.14170263707637787, + "confidence": 0.3, + "words": [ + { + "text": "dans", + "start": 8.9, + "end": 9.04, + "confidence": 0.329 + }, + { + "text": "quelques", + "start": 9.04, + "end": 9.26, + "confidence": 0.282 + }, + { + "text": "interagues", + "start": 9.26, + "end": 10.18, + "confidence": 0.238 + }, + { + "text": "entraîne.", + "start": 10.18, + "end": 10.84, + "confidence": 0.421 + } + ] + }, + { + "id": 4, + "seek": 0, + "start": 11.04, + "end": 12.92, + "text": " Et il est d'ailleurs, c'est la photo c'est hyper convaincant.", + "tokens": [ + 3790, + 1930, + 871, + 274, + 6, + 19400, + 11, + 269, + 6, + 377, + 635, + 5052, + 269, + 6, + 377, + 9848, + 3754, + 491, + 66, + 394, + 13 + ], + "temperature": 0.0, + 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}, + { + "id": 5, + "seek": 0, + "start": 13.26, + "end": 18.03, + "text": " Alors évidemment, il faudrait ajouter les interfaces les grand-attêtes qu'il a été beaucoup", + "tokens": [ + 9946, + 24724, + 11, + 1930, + 38694, + 8645, + 17680, + 23985, + 1512, + 28416, + 1512, + 2697, + 12, + 1591, + 38262, + 421, + 6, + 388, + 257, + 8862, + 8796 + ], + "temperature": 0.0, + "avg_logprob": -0.566579490710216, + "compression_ratio": 1.605421686746988, + "no_speech_prob": 0.14170263707637787, + "confidence": 0.553, + "words": [ + { + "text": "Alors", + "start": 13.26, + "end": 13.48, + "confidence": 0.904 + }, + { + "text": "évidemment,", + "start": 13.48, + "end": 13.92, + "confidence": 0.785 + }, + { + "text": "il", + "start": 13.92, + "end": 14.4, + "confidence": 0.961 + }, + { + "text": "faudrait", + "start": 14.4, + "end": 14.76, + "confidence": 0.85 + }, + { + "text": "ajouter", + "start": 14.76, + "end": 15.38, + "confidence": 0.874 + }, + { + "text": "les", + "start": 15.38, + "end": 15.62, + "confidence": 0.933 + }, + { + "text": "interfaces", + "start": 15.62, + "end": 15.86, + "confidence": 0.359 + }, + { + "text": "les", + "start": 15.86, + "end": 16.5, + "confidence": 0.414 + }, + { + "text": "grand-attêtes", + "start": 16.5, + "end": 16.94, + "confidence": 0.178 + }, + { + "text": "qu'il", + "start": 16.94, + "end": 17.18, + "confidence": 0.632 + }, + { + "text": "a", + "start": 17.18, + "end": 17.24, + "confidence": 0.969 + }, + { + "text": "été", + "start": 17.24, + "end": 17.5, + "confidence": 0.957 + }, + { + "text": "beaucoup", + "start": 17.5, + "end": 18.03, + "confidence": 0.572 + } + ] + }, + { + "id": 6, + "seek": 0, + "start": 18.03, + "end": 19.26, + "text": " très souvent ementionné.", + "tokens": [ + 5732, + 20847, + 846, + 1251, + 15055, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.566579490710216, + "compression_ratio": 1.605421686746988, + "no_speech_prob": 0.14170263707637787, + "confidence": 0.541, + "words": [ + { + "text": "très", + "start": 18.03, + "end": 18.66, + "confidence": 0.959 + }, + { + "text": "souvent", + "start": 18.66, + "end": 18.82, + "confidence": 0.994 + }, + { + "text": "ementionné.", + "start": 18.82, + "end": 19.26, + "confidence": 0.365 + } + ] + }, + { + "id": 7, + "seek": 0, + "start": 19.86, + "end": 23.54, + "text": " Mais bon, il faudrait que les profites aussi de 20 ans pendant l'été, les ordinateurs", + "tokens": [ + 6313, + 4428, + 11, + 1930, + 38694, + 8645, + 631, + 1512, + 1740, + 3324, + 6212, + 368, + 945, + 1567, + 17338, + 287, + 6, + 21210, + 11, + 1512, + 4792, + 13923, + 2156 + ], + "temperature": 0.0, + "avg_logprob": -0.566579490710216, + "compression_ratio": 1.605421686746988, + "no_speech_prob": 0.14170263707637787, + "confidence": 0.648, + "words": [ + { + "text": "Mais", + "start": 19.86, + "end": 20.22, + "confidence": 0.975 + }, + { + "text": "bon,", + "start": 20.22, + "end": 20.56, + "confidence": 0.479 + }, + { + "text": "il", + "start": 20.56, + "end": 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"end": 23.54, + "confidence": 0.934 + } + ] + }, + { + "id": 8, + "seek": 0, + "start": 23.58, + "end": 25.26, + "text": " nous ont appris à piquer sur des icônes.", + "tokens": [ + 4666, + 6592, + 724, + 5714, + 1531, + 280, + 23909, + 1022, + 730, + 4376, + 2851, + 4081, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.566579490710216, + "compression_ratio": 1.605421686746988, + "no_speech_prob": 0.14170263707637787, + "confidence": 0.663, + "words": [ + { + "text": "nous", + "start": 23.58, + "end": 23.74, + "confidence": 0.833 + }, + { + "text": "ont", + "start": 23.74, + "end": 23.86, + "confidence": 0.976 + }, + { + "text": "appris", + "start": 23.86, + "end": 24.06, + "confidence": 0.947 + }, + { + "text": "à", + "start": 24.06, + "end": 24.24, + "confidence": 0.24 + }, + { + "text": "piquer", + "start": 24.24, + "end": 24.42, + "confidence": 0.45 + }, + { + "text": "sur", + "start": 24.42, + "end": 24.68, + "confidence": 0.749 + }, + { + "text": "des", + "start": 24.68, + "end": 24.8, + "confidence": 0.96 + }, + { + "text": "icônes.", + "start": 24.8, + "end": 25.26, + "confidence": 0.656 + } + ] + }, + { + "id": 9, + "seek": 2556, + "start": 25.58, + "end": 30.56, + "text": " C'est ce que le smartphone ajoute le toucher, qui rend le contact plus direct, plus sensible.", + "tokens": [ + 383, + 6, + 377, + 1769, + 631, + 476, + 13307, + 17680, + 14040, + 476, + 2557, + 260, + 11, + 1956, + 6125, + 476, + 3385, + 1804, + 2047, + 11, + 1804, + 25380, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.4095459938049316, + "compression_ratio": 1.7522658610271904, + "no_speech_prob": 0.0006256799097172916, + "confidence": 0.643, + "words": [ + { + "text": "C'est", + "start": 25.58, + "end": 25.66, + "confidence": 0.449 + }, + { + "text": "ce", + "start": 25.66, + "end": 25.72, + "confidence": 0.491 + }, + { + "text": "que", + "start": 25.72, + "end": 25.94, + "confidence": 0.935 + }, + { + "text": "le", + "start": 25.94, + "end": 26.6, + "confidence": 0.377 + 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"confidence": 0.332 + } + ] + }, + { + "id": 10, + "seek": 2556, + "start": 31.04, + "end": 34.34, + "text": " Et puis, évidemment, il faudrait parler aussi des applications qui permettent de contourner", + "tokens": [ + 3790, + 9093, + 11, + 24724, + 11, + 1930, + 38694, + 8645, + 16421, + 6212, + 730, + 5821, + 1956, + 21540, + 317, + 368, + 21234, + 1193 + ], + "temperature": 0.0, + "avg_logprob": -0.4095459938049316, + "compression_ratio": 1.7522658610271904, + "no_speech_prob": 0.0006256799097172916, + "confidence": 0.827, + "words": [ + { + "text": "Et", + "start": 31.04, + "end": 31.24, + "confidence": 0.914 + }, + { + "text": "puis,", + "start": 31.24, + "end": 31.34, + "confidence": 0.713 + }, + { + "text": "évidemment,", + "start": 31.34, + "end": 31.64, + "confidence": 0.378 + }, + { + "text": "il", + "start": 31.64, + "end": 31.78, + "confidence": 0.935 + }, + { + "text": "faudrait", + "start": 31.78, + "end": 31.88, + "confidence": 0.99 + }, + { + "text": "parler", + 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13, + "seek": 2556, + "start": 43.1, + "end": 46.48, + "text": " dit qu'il est très fondablement inédit dans l'histoire de l'humanité.", + "tokens": [ + 6176, + 421, + 6, + 388, + 871, + 5732, + 9557, + 712, + 518, + 294, + 7811, + 270, + 2680, + 287, + 6, + 29093, + 368, + 287, + 6, + 18796, + 5066, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.4095459938049316, + "compression_ratio": 1.7522658610271904, + "no_speech_prob": 0.0006256799097172916, + "confidence": 0.768, + "words": [ + { + "text": "dit", + "start": 43.1, + "end": 43.52, + "confidence": 0.551 + }, + { + "text": "qu'il", + "start": 43.52, + "end": 43.68, + "confidence": 0.969 + }, + { + "text": "est", + "start": 43.68, + "end": 43.8, + "confidence": 0.851 + }, + { + "text": "très", + "start": 43.8, + "end": 43.94, + "confidence": 0.368 + }, + { + "text": "fondablement", + "start": 43.94, + "end": 44.68, + "confidence": 0.593 + }, + { + "text": "inédit", + "start": 44.68, + "end": 45.52, + "confidence": 0.66 + }, + { + "text": "dans", + "start": 45.52, + "end": 45.74, + "confidence": 0.778 + }, + { + "text": "l'histoire", + "start": 45.74, + "end": 45.98, + "confidence": 0.825 + }, + { + "text": "de", + "start": 45.98, + "end": 46.08, + "confidence": 0.978 + }, + { + "text": "l'humanité.", + "start": 46.08, + "end": 46.48, + "confidence": 0.991 + } + ] + }, + { + "id": 14, + "seek": 2556, + "start": 47.06, + "end": 48.76, + "text": " Mais ça s'assoulait d'une autre interrogation.", + "tokens": [ + 6313, + 2788, + 262, + 6, + 640, + 263, + 35235, + 274, + 6, + 2613, + 15081, + 24871, + 399, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.4095459938049316, + "compression_ratio": 1.7522658610271904, + "no_speech_prob": 0.0006256799097172916, + "confidence": 0.697, + "words": [ + { + "text": "Mais", + "start": 47.06, + "end": 47.16, + "confidence": 0.939 + }, + { + "text": "ça", + "start": 47.16, + "end": 47.46, + "confidence": 0.854 + }, + { + "text": "s'assoulait", + "start": 47.46, + "end": 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"start": 55.6, + "end": 58.6, + "text": " Je veux dire, est-ce que le rapport qu'on a au sein de foi n'est comparable à celui", + "tokens": [ + 2588, + 16389, + 1264, + 11, + 871, + 12, + 384, + 631, + 476, + 18018, + 421, + 6, + 266, + 257, + 1609, + 6195, + 368, + 6901, + 297, + 6, + 377, + 6311, + 712, + 1531, + 22829 + ], + "temperature": 0.0, + "avg_logprob": -0.6093524909167556, + "compression_ratio": 1.6292834890965733, + "no_speech_prob": 6.752492481609806e-05, + "confidence": 0.626, + "words": [ + { + "text": "Je", + "start": 55.6, + "end": 55.84, + "confidence": 0.335 + }, + { + "text": "veux", + "start": 55.84, + "end": 55.94, + "confidence": 0.432 + }, + { + "text": "dire,", + "start": 55.94, + "end": 56.16, + "confidence": 0.992 + }, + { + "text": "est-ce", + "start": 56.16, + "end": 56.34, + "confidence": 0.951 + }, + { + "text": "que", + "start": 56.34, + "end": 56.4, + "confidence": 0.973 + }, + { + "text": "le", + "start": 56.4, + "end": 56.54, + "confidence": 0.987 + 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qu'on entretenait à d'autres objectes techniques comme la voiture ou le téléphone?", + "tokens": [ + 421, + 6, + 266, + 3962, + 1147, + 1001, + 1531, + 274, + 6, + 16752, + 2657, + 279, + 7512, + 5173, + 635, + 38859, + 2820, + 476, + 47159, + 2506 + ], + "temperature": 0.0, + "avg_logprob": -0.6093524909167556, + "compression_ratio": 1.6292834890965733, + "no_speech_prob": 6.752492481609806e-05, + "confidence": 0.781, + "words": [ + { + "text": "qu'on", + "start": 58.72, + "end": 58.88, + "confidence": 0.941 + }, + { + "text": "entretenait", + "start": 58.88, + "end": 59.38, + "confidence": 0.657 + }, + { + "text": "à", + "start": 59.38, + "end": 59.44, + "confidence": 0.973 + }, + { + "text": "d'autres", + "start": 59.44, + "end": 59.64, + "confidence": 0.909 + }, + { + "text": "objectes", + "start": 59.64, + "end": 60.02, + "confidence": 0.528 + }, + { + "text": "techniques", + "start": 60.02, + "end": 60.38, + "confidence": 0.547 + }, + { + "text": "comme", + "start": 60.38, + "end": 60.86, + "confidence": 0.662 + }, + { + "text": "la", + "start": 60.86, + "end": 61.46, + "confidence": 0.898 + }, + { + "text": "voiture", + "start": 61.46, + "end": 61.8, + "confidence": 0.954 + }, + { + "text": "ou", + "start": 61.8, + "end": 62.32, + "confidence": 0.74 + }, + { + "text": "le", + "start": 62.32, + "end": 62.6, + "confidence": 0.847 + }, + { + "text": "téléphone?", + "start": 62.6, + "end": 62.81, + "confidence": 0.979 + } + ] + }, + { + "id": 19, + "seek": 5548, + "start": 62.81, + "end": 66.07, + "text": " Il n'y a pas d'équivalent.", + "tokens": [ + 4416, + 297, + 6, + 88, + 257, + 1736, + 274, + 6, + 20183, + 3576, + 317, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.6093524909167556, + "compression_ratio": 1.6292834890965733, + "no_speech_prob": 6.752492481609806e-05, + "confidence": 0.882, + "words": [ + { + "text": "Il", + "start": 62.81, + "end": 65.42, + "confidence": 0.866 + }, + { + "text": "n'y", + "start": 65.42, + "end": 65.52, + 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0.233 + }, + { + "text": "de", + "start": 67.46, + "end": 67.58, + "confidence": 0.963 + }, + { + "text": "nous", + "start": 67.58, + "end": 67.8, + "confidence": 0.631 + }, + { + "text": "voter", + "start": 67.8, + "end": 68.24, + "confidence": 0.241 + }, + { + "text": "dans", + "start": 68.24, + "end": 68.68, + "confidence": 0.853 + }, + { + "text": "la", + "start": 68.68, + "end": 68.88, + "confidence": 0.61 + }, + { + "text": "relation", + "start": 68.88, + "end": 69.22, + "confidence": 0.932 + }, + { + "text": "à", + "start": 69.22, + "end": 69.34, + "confidence": 0.792 + }, + { + "text": "l'objet.", + "start": 69.34, + "end": 69.74, + "confidence": 0.889 + } + ] + }, + { + "id": 21, + "seek": 5548, + "start": 70.18, + "end": 74.78, + "text": " C'est facilement éterréciant parce qu'on a impression de, comme le 10, les utilisateurs", + "tokens": [ + 383, + 6, + 377, + 23670, + 518, + 1136, + 391, + 10521, + 537, + 394, + 6992, + 421, + 6, + 266, + 257, + 9995, + 368, + 11, + 5173, 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+ "id": 24, + "seek": 8298, + "start": 83.0, + "end": 87.66, + "text": " le jeu. Donc, à objets inédits, rapport inédits.", + "tokens": [ + 476, + 16748, + 13, + 7477, + 11, + 1531, + 1111, + 25349, + 294, + 7811, + 1208, + 11, + 18018, + 294, + 7811, + 1208, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.4346100035167876, + "compression_ratio": 1.5907335907335907, + "no_speech_prob": 3.121094050584361e-05, + "confidence": 0.614, + "words": [ + { + "text": "le", + "start": 83.0, + "end": 83.12, + "confidence": 0.128 + }, + { + "text": "jeu.", + "start": 83.12, + "end": 83.64, + "confidence": 0.505 + }, + { + "text": "Donc,", + "start": 83.64, + "end": 84.48, + "confidence": 0.513 + }, + { + "text": "à", + "start": 84.48, + "end": 84.86, + "confidence": 0.634 + }, + { + "text": "objets", + "start": 84.86, + "end": 85.36, + "confidence": 0.547 + }, + { + "text": "inédits,", + "start": 85.36, + "end": 86.24, + "confidence": 0.73 + }, + { + "text": "rapport", + "start": 86.24, + "end": 86.62, + "confidence": 0.928 + }, + { + "text": "inédits.", + "start": 86.62, + "end": 87.66, + "confidence": 0.921 + } + ] + }, + { + "id": 25, + "seek": 8298, + "start": 88.08, + "end": 93.78, + "text": " Et, ce rapport, si j'en prends Nicolas, frère caractérisée par un mélange de dépenses", + "tokens": [ + 3790, + 11, + 1769, + 18018, + 11, + 1511, + 361, + 6, + 268, + 46750, + 38268, + 11, + 431, + 4212, + 1032, + 578, + 4198, + 50027, + 971, + 517, + 41953, + 933, + 368, + 27998, + 9085 + ], + "temperature": 0.0, + "avg_logprob": -0.4346100035167876, + "compression_ratio": 1.5907335907335907, + "no_speech_prob": 3.121094050584361e-05, + "confidence": 0.624, + "words": [ + { + "text": "Et,", + "start": 88.08, + "end": 88.3, + "confidence": 0.87 + }, + { + "text": "ce", + "start": 88.3, + "end": 88.8, + "confidence": 0.462 + }, + { + "text": "rapport,", + "start": 88.8, + "end": 89.28, + "confidence": 0.997 + }, + { + "text": "si", + "start": 89.28, + "end": 89.56, + "confidence": 0.913 + }, + { + "text": "j'en", + "start": 89.56, + "end": 89.74, + 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-0.4346100035167876, + "compression_ratio": 1.5907335907335907, + "no_speech_prob": 3.121094050584361e-05, + "confidence": 0.583, + "words": [ + { + "text": "et", + "start": 94.36, + "end": 94.52, + "confidence": 0.986 + }, + { + "text": "de", + "start": 94.52, + "end": 94.56, + "confidence": 0.996 + }, + { + "text": "rojets.", + "start": 94.56, + "end": 94.98, + "confidence": 0.41 + } + ] + }, + { + "id": 27, + "seek": 8298, + "start": 95.8, + "end": 100.4, + "text": " Bon, en vrai, il faudrait remonter très très finement toute l'histoire des objectes", + "tokens": [ + 7368, + 11, + 465, + 17815, + 11, + 1930, + 38694, + 8645, + 890, + 41806, + 5732, + 5732, + 962, + 1712, + 14953, + 287, + 6, + 29093, + 730, + 2657, + 279 + ], + "temperature": 0.0, + "avg_logprob": -0.4346100035167876, + "compression_ratio": 1.5907335907335907, + "no_speech_prob": 3.121094050584361e-05, + "confidence": 0.749, + "words": [ + { + "text": "Bon,", + "start": 95.8, + "end": 96.06, + "confidence": 0.71 + 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"confidence": 0.805 + } + ] + }, + { + "id": 28, + "seek": 8298, + "start": 100.4, + "end": 105.14, + "text": " techniques et de leur infération dans le vie pour déterminer si ce rapport est totalement", + "tokens": [ + 7512, + 1030, + 368, + 9580, + 1536, + 526, + 2405, + 2680, + 476, + 4941, + 2016, + 2795, + 29725, + 260, + 1511, + 1769, + 18018, + 871, + 45203 + ], + "temperature": 0.0, + "avg_logprob": -0.4346100035167876, + "compression_ratio": 1.5907335907335907, + "no_speech_prob": 3.121094050584361e-05, + "confidence": 0.665, + "words": [ + { + "text": "techniques", + "start": 100.4, + "end": 101.02, + "confidence": 0.954 + }, + { + "text": "et", + "start": 101.02, + "end": 101.52, + "confidence": 0.967 + }, + { + "text": "de", + "start": 101.52, + "end": 101.64, + "confidence": 0.973 + }, + { + "text": "leur", + "start": 101.64, + "end": 101.78, + "confidence": 0.811 + }, + { + "text": "infération", + "start": 101.78, + "end": 102.22, + "confidence": 0.227 + }, + { + "text": "dans", + "start": 102.22, + "end": 102.46, + "confidence": 0.518 + }, + { + "text": "le", + "start": 102.46, + "end": 102.54, + "confidence": 0.511 + }, + { + "text": "vie", + "start": 102.54, + "end": 102.78, + "confidence": 0.612 + }, + { + "text": "pour", + "start": 102.78, + "end": 103.06, + "confidence": 0.933 + }, + { + "text": "déterminer", + "start": 103.06, + "end": 103.64, + "confidence": 0.954 + }, + { + "text": "si", + "start": 103.64, + "end": 103.74, + "confidence": 0.488 + }, + { + "text": "ce", + "start": 103.74, + "end": 103.86, + "confidence": 0.98 + }, + { + "text": "rapport", + "start": 103.86, + "end": 104.1, + "confidence": 0.997 + }, + { + "text": "est", + "start": 104.1, + "end": 104.88, + "confidence": 0.942 + }, + { + "text": "totalement", + "start": 104.88, + "end": 105.14, + "confidence": 0.854 + } + ] + }, + { + "id": 29, + "seek": 8298, + "start": 105.26, + "end": 105.78, + "text": " inédit.", + "tokens": [ + 294, + 7811, + 270, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.4346100035167876, + "compression_ratio": 1.5907335907335907, + "no_speech_prob": 3.121094050584361e-05, + "confidence": 0.943, + "words": [ + { + "text": "inédit.", + "start": 105.26, + "end": 105.78, + "confidence": 0.943 + } + ] + }, + { + "id": 30, + "seek": 8298, + "start": 106.14, + "end": 109.36, + "text": " Mais j'ai l'impression comme ça que Nicolas se trompe pas vraiment.", + "tokens": [ + 6313, + 361, + 6, + 1301, + 287, + 6, + 36107, + 5173, + 2788, + 631, + 38268, + 369, + 504, + 298, + 494, + 1736, + 8322, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.4346100035167876, + "compression_ratio": 1.5907335907335907, + "no_speech_prob": 3.121094050584361e-05, + "confidence": 0.798, + "words": [ + { + "text": "Mais", + "start": 106.14, + "end": 106.34, + "confidence": 0.872 + }, + { + "text": "j'ai", + "start": 106.34, + "end": 106.9, + "confidence": 0.924 + }, + { + "text": "l'impression", + "start": 106.9, + "end": 107.28, + "confidence": 0.967 + 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Il y a eu plein de discussions autour de la voiture ou même", + "tokens": [ + 8732, + 34081, + 11, + 1506, + 262, + 6000, + 13, + 4416, + 288, + 257, + 2228, + 21088, + 368, + 11088, + 30249, + 368, + 635, + 38859, + 2820, + 5698 + ], + "temperature": 0.0, + "avg_logprob": -0.394765736144266, + "compression_ratio": 1.7249190938511327, + "no_speech_prob": 9.048193533089943e-06, + "confidence": 0.829, + "words": [ + { + "text": "Pour", + "start": 109.72, + "end": 110.08, + "confidence": 0.92 + }, + { + "text": "autant,", + "start": 110.08, + "end": 110.36, + "confidence": 0.986 + }, + { + "text": "je", + "start": 110.36, + "end": 110.4, + "confidence": 0.894 + }, + { + "text": "sache.", + "start": 110.4, + "end": 110.86, + "confidence": 0.531 + }, + { + "text": "Il", + "start": 110.86, + "end": 111.16, + "confidence": 0.851 + }, + { + "text": "y", + "start": 111.16, + "end": 111.22, + "confidence": 0.872 + }, + { + "text": "a", + "start": 111.22, + "end": 111.28, + "confidence": 0.939 + }, + { + "text": "eu", + "start": 111.28, + "end": 111.38, + "confidence": 0.891 + }, + { + "text": "plein", + "start": 111.38, + "end": 111.76, + "confidence": 0.833 + }, + { + "text": "de", + "start": 111.76, + "end": 112.04, + "confidence": 0.94 + }, + { + "text": "discussions", + "start": 112.04, + "end": 112.46, + "confidence": 0.711 + }, + { + "text": "autour", + "start": 112.46, + "end": 112.96, + "confidence": 0.97 + }, + { + "text": "de", + "start": 112.96, + "end": 113.46, + "confidence": 0.952 + }, + { + "text": "la", + "start": 113.46, + "end": 113.5, + "confidence": 0.955 + }, + { + "text": "voiture", + "start": 113.5, + "end": 113.8, + "confidence": 0.983 + }, + { + "text": "ou", + "start": 113.8, + "end": 114.02, + "confidence": 0.523 + }, + { + "text": "même", + "start": 114.02, + "end": 114.26, + "confidence": 0.963 + } + ] + }, + { + "id": 32, + "seek": 10970, + "start": 114.42, + "end": 118.76, + "text": " du téléphone. Mais la dépense n'était pas du même mort, donc le rejet n'en", + "tokens": [ + 1581, + 47159, + 13, + 6313, + 635, + 27998, + 1288, + 297, + 6, + 9743, + 1736, + 1581, + 5698, + 6599, + 11, + 5926, + 476, + 319, + 7108, + 297, + 6, + 268 + ], + "temperature": 0.0, + "avg_logprob": -0.394765736144266, + "compression_ratio": 1.7249190938511327, + "no_speech_prob": 9.048193533089943e-06, + "confidence": 0.732, + "words": [ + { + "text": "du", + "start": 114.42, + "end": 114.6, + "confidence": 0.677 + }, + { + "text": "téléphone.", + "start": 114.6, + "end": 115.16, + "confidence": 0.983 + }, + { + "text": "Mais", + "start": 115.16, + "end": 115.72, + "confidence": 0.649 + }, + { + "text": "la", + "start": 115.72, + "end": 116.0, + "confidence": 0.809 + }, + { + "text": "dépense", + "start": 116.0, + "end": 116.38, + "confidence": 0.766 + }, + { + "text": "n'était", + "start": 116.38, + "end": 116.62, + "confidence": 0.952 + }, + { + "text": "pas", + "start": 116.62, + "end": 117.02, + 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"pour", + "start": 135.76, + "end": 135.94, + "confidence": 0.983 + }, + { + "text": "discuter", + "start": 135.94, + "end": 136.26, + "confidence": 0.882 + }, + { + "text": "avec", + "start": 136.26, + "end": 136.44, + "confidence": 0.993 + }, + { + "text": "un", + "start": 136.44, + "end": 136.6, + "confidence": 0.976 + }, + { + "text": "copain.", + "start": 136.6, + "end": 136.84, + "confidence": 0.948 + } + ] + }, + { + "id": 39, + "seek": 13702, + "start": 137.26, + "end": 141.8, + "text": " Mais ça ne ressemble pas à ce qu'on peut ressentir à voir même mome aujourd'hui", + "tokens": [ + 6313, + 2788, + 408, + 725, + 37227, + 1736, + 1531, + 1769, + 421, + 6, + 266, + 5977, + 24689, + 317, + 347, + 1531, + 10695, + 5698, + 275, + 423, + 14023, + 6, + 10556 + ], + "temperature": 0.0, + "avg_logprob": -0.5734858703613281, + "compression_ratio": 1.5562700964630225, + "no_speech_prob": 3.1260256037057843e-06, + "confidence": 0.716, + "words": [ + { + "text": "Mais", + "start": 137.26, 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lâcher à l'éantrénée, ça m'a eu immédiate.", + "tokens": [ + 1279, + 4212, + 368, + 287, + 6, + 686, + 15970, + 271, + 368, + 48835, + 6759, + 1531, + 287, + 6, + 526, + 394, + 81, + 3516, + 3856, + 11, + 2788, + 275, + 6, + 64, + 2228, + 3397, + 526, + 4504, + 473, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.5734858703613281, + "compression_ratio": 1.5562700964630225, + "no_speech_prob": 3.1260256037057843e-06, + "confidence": 0.401, + "words": [ + { + "text": "extère", + "start": 145.94, + "end": 146.38, + "confidence": 0.357 + }, + { + "text": "de", + "start": 146.38, + "end": 146.46, + "confidence": 0.253 + }, + { + "text": "l'intempis", + "start": 146.46, + "end": 146.7, + "confidence": 0.153 + }, + { + "text": "de", + "start": 146.7, + "end": 146.9, + "confidence": 0.858 + }, + { + "text": "lâcher", + "start": 146.9, + "end": 147.32, + "confidence": 0.824 + }, + { + "text": "à", + "start": 147.32, + "end": 147.44, + "confidence": 0.494 + }, + { + "text": "l'éantrénée,", + 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{ + "text": "aussi.", + "start": 151.7, + "end": 152.02, + "confidence": 0.145 + } + ] + }, + { + "id": 43, + "seek": 13702, + "start": 152.66, + "end": 154.4, + "text": " Donc, rapport immédiate d'accord.", + "tokens": [ + 7477, + 11, + 18018, + 3397, + 526, + 4504, + 473, + 274, + 6, + 19947, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.5734858703613281, + "compression_ratio": 1.5562700964630225, + "no_speech_prob": 3.1260256037057843e-06, + "confidence": 0.851, + "words": [ + { + "text": "Donc,", + "start": 152.66, + "end": 153.0, + "confidence": 0.985 + }, + { + "text": "rapport", + "start": 153.0, + "end": 153.42, + "confidence": 0.977 + }, + { + "text": "immédiate", + "start": 153.42, + "end": 154.26, + "confidence": 0.825 + }, + { + "text": "d'accord.", + "start": 154.26, + "end": 154.4, + "confidence": 0.806 + } + ] + }, + { + "id": 44, + "seek": 13702, + "start": 154.4, + "end": 157.95, + "text": " Mais pourquoi, à ton impression qu'on en sortira jamais?", + "tokens": [ 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merveilleux.", + "tokens": [ + 7955, + 3551, + 303, + 3409, + 2449, + 1030, + 33227, + 401, + 1925, + 11, + 1956, + 257, + 6176, + 1531, + 748, + 285, + 1925, + 971, + 45781, + 11, + 3551, + 303, + 3409, + 2449, + 13 + ], + "temperature": 0.0, + "avg_logprob": -0.7643054464588994, + "compression_ratio": 1.544041450777202, + "no_speech_prob": 3.89045562769752e-05, + "confidence": 0.397, + "words": [ + { + "text": "route", + "start": 162.37, + "end": 162.6, + "confidence": 0.076 + }, + { + "text": "merveilleux", + "start": 162.6, + "end": 163.3, + "confidence": 0.635 + }, + { + "text": "et", + "start": 163.3, + "end": 163.42, + "confidence": 0.837 + }, + { + "text": "diabolique,", + "start": 163.42, + "end": 163.82, + "confidence": 0.328 + }, + { + "text": "qui", + "start": 163.82, + "end": 163.9, + "confidence": 0.365 + }, + { + "text": "a", + "start": 163.9, + "end": 163.98, + "confidence": 0.054 + }, + { + "text": "dit", + "start": 163.98, + "end": 164.06, + "confidence": 0.085 + }, + 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a/tests/expected/tiny_fr/radio_short.mp3.words.json b/tests/expected/tiny_fr/radio_short.mp3.words.json new file mode 100644 index 0000000000000000000000000000000000000000..b7006f9b2e7859513b6b1c89436472eaeeecb772 --- /dev/null +++ b/tests/expected/tiny_fr/radio_short.mp3.words.json @@ -0,0 +1,106 @@ +{ + "text": " ... ... ... ...", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.44, + "end": 1.46, + "text": " ...", + "tokens": [ + 50364, + 1097, + 50614 + ], + "temperature": 0.0, + "avg_logprob": -1.420121431350708, + "compression_ratio": 0.2727272727272727, + "no_speech_prob": 0.5095687508583069, + "confidence": 0.224, + "words": [ + { + "text": "...", + "start": 0.44, + "end": 1.46, + "confidence": 0.224 + } + ] + }, + { + "id": 1, + "seek": 6000, + "start": 60.0, + "end": 69.42, + "text": " ...", + "tokens": [ + 50364, + 1097, + 51714 + ], + "temperature": 0.0, + "avg_logprob": -0.965411365032196, + "compression_ratio": 0.2727272727272727, + "no_speech_prob": 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--git a/tests/expected/tiny_fr/smartphone.mp3.words.json b/tests/expected/tiny_fr/smartphone.mp3.words.json new file mode 100644 index 0000000000000000000000000000000000000000..c4c22c2b044b299c716373c8421ba2b1f620cc0c --- /dev/null +++ b/tests/expected/tiny_fr/smartphone.mp3.words.json @@ -0,0 +1,5091 @@ +{ + "text": " C'est évidence que dit Nicolas, mais je me l'étais jamais formulé comme ça. Ce qui fait la force du smartphone, c'est pas seulement la cumulation des fonctions, mais la manière dans quelques interagues entraîne. Et il est d'ailleurs, c'est la photo c'est hyper convaincant. Alors évidemment, il faudrait ajouter les interfaces les grand-attachilles à été beaucoup très souvent mentionnées. Mais bon, il faudrait que les profites aussi de 20 ans pendant l'été, les ordinateurs nous ont appris à piquer sur des icônes, sauf que, alors le smartphone ajoute le toucher, qui rend le contact plus direct, plus sensible. Et puis, évidemment, il faudrait parler aussi des applications qui permettent de contourner le côté tout flu de la navigation web pour aller directement en but. Bref, tout ça, ce sont les conditions qui permettent de créer cette objet, en Nicolas, dit qu'il est très symbolablement inédit dans l'histoire de l'humanité. Mais ça s'assoulait d'une autre interrogation. Est-ce que le fait que cette objet soit inédit un d'huits que notre rapport a lui est aussi un rapport inédit ? Est-ce que le rapport qu'on a au sein de foi n'est comparable à celui qu'on entretenait à d'autres objectes techniques comme la voiture ou le téléphone ? Il n'y a pas d'équivalent. On s'est espèrent de nous voter dans la relation à l'objet. C'est facilement éterricion. Parce que la passion de l'utilisateur et ses affices a dépendance, cette objet d'un lieu en fait, une espèce de relation de médiation avec le monde qui rendent encore avec la maille de celles formes de rogeur. Donc, à objets inédits, rapport inédits. Et, ce rapport, si j'en prends Nicolas, frère caractérisée par un mélange de dépendance et de rogeur. Bon, en vrai, il faudrait remonter très, très filmant tout l'histoire des objectes techniques et de leur infertion dans nos vieux pour déterminer si ce rapport est totalement inédit. Mais j'ai l'impression comme ça que Nicolas se trompe pas vraiment. Pour autant, je sache. Il y a eu plein de discussions autour de la voiture ou même du téléphone. Mais, la dépense n'était pas du même mort, donc le rejet n'en plus n'était pas du même mort. On peut adorer sa bagnure. On a par besoin pour plein de choses. Et là, le soir, quand on va se coucher, on la laisse. On la pade en la main quand on est colis, qu'on n'a même pas au chiot. On pouvait être émervé par son mome qui occupeait la ligne de téléphone pendant une heure chaque soir pour discuter avec un copain. Mais ça ne ressemble pas à ce qu'on peut ressentir à voir même mome aujourd'hui. Continuellement avec son smartphone dans la main, comme c'était une sorte de estimateur extère de tomber de lâcher à l'éantrénée, ça m'a eu immédiate. Bon, je dis ça pour le mome, mais évidemment, va là, bon aussi. Donc, rapport immédiate d'accord. Mais pourquoi, à ton impression qu'on en sortira, j'amé? Et puis, il faut en remettre la faute sur les gens qui ont créé cette critique merveilleux et diabolique et diabolique par que merveilleux. Les économistes parlent de dépendance du santé. Ces vidéos, en fait, on est un santé qui a été étabis, un soit mon termine, en marchand dessus, soit des finissants débordes, des finissants, une signalétique.", + "segments": [ + { + "id": 0, + "seek": 0, + "start": 0.42, + "end": 3.66, + "text": " C'est évidence que dit Nicolas, mais je me l'étais jamais formulé comme ça.", + "tokens": [ + 50364, + 383, + 6, + 377, + 20090, + 2778, + 631, + 6176, + 38268, + 11, + 2420, + 1506, + 385, + 287, + 6, + 22824, + 14540, + 49990, + 526, + 5173, + 2788, + 13, + 50545 + ], + "temperature": 0.0, + "avg_logprob": -0.5387768369732481, + "compression_ratio": 1.6505681818181819, + "no_speech_prob": 0.14262977242469788, + "confidence": 0.709, + "words": [ + { + "text": "C'est", + "start": 0.42, + "end": 0.68, + "confidence": 0.85 + }, + { + "text": "évidence", + "start": 0.68, + "end": 0.94, + "confidence": 0.368 + }, + { + "text": "que", + "start": 0.94, + "end": 1.08, + "confidence": 0.882 + }, + { + "text": "dit", + "start": 1.08, + "end": 1.2, + 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le côté", + "tokens": [ + 50496, + 3790, + 9093, + 11, + 24724, + 11, + 1930, + 38694, + 8645, + 16421, + 6212, + 730, + 5821, + 1956, + 21540, + 317, + 368, + 21234, + 1193, + 476, + 18437, + 50698 + ], + "temperature": 0.0, + "avg_logprob": -0.4260108065442974, + "compression_ratio": 1.7156549520766773, + "no_speech_prob": 0.1274678260087967, + "confidence": 0.775, + "words": [ + { + "text": "Et", + "start": 31.1, + "end": 31.24, + "confidence": 0.949 + }, + { + "text": "puis,", + "start": 31.24, + "end": 31.36, + "confidence": 0.725 + }, + { + "text": "évidemment,", + "start": 31.42, + "end": 31.62, + "confidence": 0.211 + }, + { + "text": "il", + "start": 31.7, + "end": 31.76, + "confidence": 0.959 + }, + { + "text": "faudrait", + "start": 31.76, + "end": 31.94, + "confidence": 0.994 + }, + { + "text": "parler", + "start": 31.94, + "end": 32.14, + "confidence": 0.847 + }, + { + "text": "aussi", + "start": 32.14, + "end": 32.36, + "confidence": 0.924 + }, + { + "text": "des", + 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37.86, + "confidence": 0.768 + } + ] + }, + { + "id": 11, + "seek": 2804, + "start": 38.78, + "end": 43.13, + "text": " Bref, tout ça, ce sont les conditions qui permettent de créer cette objet, en Nicolas,", + "tokens": [ + 50860, + 49957, + 11, + 3486, + 2788, + 11, + 1769, + 4900, + 1512, + 4487, + 1956, + 21540, + 317, + 368, + 32062, + 5550, + 14964, + 11, + 465, + 38268, + 11, + 51121 + ], + "temperature": 0.0, + "avg_logprob": -0.4260108065442974, + "compression_ratio": 1.7156549520766773, + "no_speech_prob": 0.1274678260087967, + "confidence": 0.738, + "words": [ + { + "text": "Bref,", + "start": 38.78, + "end": 38.8, + "confidence": 0.972 + }, + { + "text": "tout", + "start": 38.84, + "end": 39.04, + "confidence": 0.816 + }, + { + "text": "ça,", + "start": 39.04, + "end": 39.46, + "confidence": 0.984 + }, + { + "text": "ce", + "start": 39.54, + "end": 39.76, + "confidence": 0.905 + }, + { + "text": "sont", + "start": 39.76, + "end": 39.96, + "confidence": 0.981 + }, + { + "text": "les", + "start": 39.96, + "end": 40.1, + "confidence": 0.982 + }, + { + "text": "conditions", + "start": 40.1, + "end": 40.64, + "confidence": 0.957 + }, + { + "text": "qui", + "start": 40.64, + "end": 40.96, + "confidence": 0.995 + }, + { + "text": "permettent", + "start": 40.96, + "end": 41.58, + "confidence": 0.993 + }, + { + "text": "de", + "start": 41.58, + "end": 41.64, + "confidence": 0.993 + }, + { + "text": "créer", + "start": 41.64, + "end": 42.08, + "confidence": 0.909 + }, + { + "text": "cette", + "start": 42.08, + "end": 42.34, + "confidence": 0.477 + }, + { + "text": "objet,", + "start": 42.34, + "end": 42.64, + "confidence": 0.237 + }, + { + "text": "en", + "start": 42.7, + "end": 42.84, + "confidence": 0.22 + }, + { + "text": "Nicolas,", + "start": 42.84, + "end": 43.13, + "confidence": 0.539 + } + ] + }, + { + "id": 12, + "seek": 2804, + "start": 43.13, + "end": 46.58, + "text": " dit qu'il est très symbolablement inédit dans l'histoire de l'humanité.", + 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45.74, + "end": 46.02, + "confidence": 0.825 + }, + { + "text": "de", + "start": 46.02, + "end": 46.14, + "confidence": 0.984 + }, + { + "text": "l'humanité.", + "start": 46.14, + "end": 46.58, + "confidence": 0.99 + } + ] + }, + { + "id": 13, + "seek": 2804, + "start": 47.06, + "end": 48.76, + "text": " Mais ça s'assoulait d'une autre interrogation.", + "tokens": [ + 51290, + 6313, + 2788, + 262, + 6, + 640, + 263, + 35235, + 274, + 6, + 2613, + 15081, + 24871, + 399, + 13, + 51402 + ], + "temperature": 0.0, + "avg_logprob": -0.4260108065442974, + "compression_ratio": 1.7156549520766773, + "no_speech_prob": 0.1274678260087967, + "confidence": 0.718, + "words": [ + { + "text": "Mais", + "start": 47.06, + "end": 47.24, + "confidence": 0.928 + }, + { + "text": "ça", + "start": 47.24, + "end": 47.48, + "confidence": 0.75 + }, + { + "text": "s'assoulait", + "start": 47.48, + "end": 47.84, + "confidence": 0.616 + }, + { + "text": "d'une", + "start": 47.84, + "end": 48.08, + "confidence": 0.675 + }, + { + "text": "autre", + "start": 48.08, + "end": 48.18, + "confidence": 0.964 + }, + { + "text": "interrogation.", + "start": 48.18, + "end": 48.76, + "confidence": 0.855 + } + ] + }, + { + "id": 14, + "seek": 2804, + "start": 49.42, + "end": 54.93, + "text": " Est-ce que le fait que cette objet soit inédit un d'huits que notre rapport a lui est aussi un rapport", + "tokens": [ + 51402, + 4410, + 12, + 384, + 631, + 476, + 3887, + 631, + 5550, + 14964, + 12703, + 294, + 7811, + 270, + 517, + 274, + 6, + 12086, + 1208, + 631, + 10349, + 18018, + 257, + 8783, + 871, + 6212, + 517, + 18018, + 51710 + ], + "temperature": 0.0, + "avg_logprob": -0.4260108065442974, + "compression_ratio": 1.7156549520766773, + "no_speech_prob": 0.1274678260087967, + "confidence": 0.704, + "words": [ + { + "text": "Est-ce", + "start": 49.42, + "end": 49.7, + "confidence": 0.919 + }, + { + "text": "que", + "start": 49.7, + "end": 49.74, + "confidence": 0.989 + }, + { + "text": "le", + "start": 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53.24, + "end": 53.5, + "confidence": 0.572 + }, + { + "text": "lui", + "start": 53.5, + "end": 53.7, + "confidence": 0.698 + }, + { + "text": "est", + "start": 53.7, + "end": 54.04, + "confidence": 0.88 + }, + { + "text": "aussi", + "start": 54.04, + "end": 54.52, + "confidence": 0.814 + }, + { + "text": "un", + "start": 54.52, + "end": 54.7, + "confidence": 0.48 + }, + { + "text": "rapport", + "start": 54.7, + "end": 54.93, + "confidence": 0.951 + } + ] + }, + { + "id": 15, + "seek": 2804, + "start": 54.93, + "end": 55.88, + "text": " inédit ?", + "tokens": [ + 51710, + 294, + 7811, + 270, + 2506, + 51760 + ], + "temperature": 0.0, + "avg_logprob": -0.4260108065442974, + "compression_ratio": 1.7156549520766773, + "no_speech_prob": 0.1274678260087967, + "confidence": 0.86, + "words": [ + { + "text": "inédit ?", + "start": 54.93, + "end": 55.88, + "confidence": 0.86 + } + ] + }, + { + "id": 16, + "seek": 5596, + "start": 55.96, + "end": 59.36, + "text": " Est-ce que le rapport qu'on a au sein de foi n'est comparable à celui qu'on entretenait", + "tokens": [ + 50364, + 4410, + 12, + 384, + 631, + 476, + 18018, + 421, + 6, + 266, + 257, + 1609, + 6195, + 368, + 6901, + 297, + 6, + 377, + 25323, + 1531, + 22829, + 421, + 6, + 266, + 3962, + 1147, + 1001, + 50530 + ], + "temperature": 0.0, + "avg_logprob": -0.6289185115269252, + "compression_ratio": 1.5749128919860627, + "no_speech_prob": 0.21948665380477905, + "confidence": 0.62, + "words": [ + { + "text": "Est-ce", + "start": 55.96, + "end": 56.38, + "confidence": 0.55 + }, + { + "text": "que", + "start": 56.38, + "end": 56.44, + "confidence": 0.892 + }, + { + "text": "le", + "start": 56.44, + "end": 56.58, + "confidence": 0.982 + }, + { + "text": "rapport", + "start": 56.58, + "end": 56.9, + "confidence": 0.999 + }, + { + "text": "qu'on", + "start": 56.9, + "end": 57.14, + "confidence": 0.904 + }, + { + "text": "a", + "start": 57.14, + "end": 57.2, + "confidence": 0.959 + }, + { + "text": "au", + "start": 57.2, + "end": 57.28, + "confidence": 0.272 + }, + { + "text": "sein", + "start": 57.28, + "end": 57.42, + "confidence": 0.17 + }, + { + "text": "de", + "start": 57.42, + "end": 57.56, + "confidence": 0.23 + }, + { + "text": "foi", + "start": 57.56, + "end": 57.58, + "confidence": 0.121 + }, + { + "text": "n'est", + "start": 57.58, + "end": 57.78, + "confidence": 0.79 + }, + { + "text": "comparable", + "start": 57.78, + "end": 58.28, + "confidence": 0.547 + }, + { + "text": "à", + "start": 58.28, + "end": 58.48, + "confidence": 0.934 + }, + { + "text": "celui", + "start": 58.48, + "end": 58.7, + "confidence": 0.851 + }, + { + "text": "qu'on", + "start": 58.7, + "end": 58.94, + "confidence": 0.926 + }, + { + "text": "entretenait", + "start": 58.94, + "end": 59.36, + "confidence": 0.56 + } + ] + }, + { + "id": 17, + "seek": 5596, + "start": 59.36, + "end": 63.14, + "text": " à d'autres objectes techniques comme la voiture ou le téléphone ?", + "tokens": [ + 50530, + 1531, + 274, + 6, + 16752, + 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"confidence": 0.912 + }, + { + "text": "téléphone ?", + "start": 62.68, + "end": 63.14, + "confidence": 0.983 + } + ] + }, + { + "id": 18, + "seek": 5596, + "start": 65.4, + "end": 66.16, + "text": " Il n'y a pas d'équivalent.", + "tokens": [ + 50714, + 4416, + 297, + 6, + 88, + 257, + 1736, + 274, + 6, + 20183, + 3576, + 317, + 13, + 50872 + ], + "temperature": 0.0, + "avg_logprob": -0.6289185115269252, + "compression_ratio": 1.5749128919860627, + "no_speech_prob": 0.21948665380477905, + "confidence": 0.881, + "words": [ + { + "text": "Il", + "start": 65.4, + "end": 65.5, + "confidence": 0.901 + }, + { + "text": "n'y", + "start": 65.5, + "end": 65.54, + "confidence": 0.859 + }, + { + "text": "a", + "start": 65.54, + "end": 65.56, + "confidence": 0.962 + }, + { + "text": "pas", + "start": 65.56, + "end": 65.68, + "confidence": 0.998 + }, + { + "text": "d'équivalent.", + "start": 65.68, + "end": 66.16, + "confidence": 0.853 + } + ] + }, + { + "id": 19, + "seek": 5596, + "start": 66.16, + "end": 69.92, + "text": " On s'est espèrent de nous voter dans la relation à l'objet.", + "tokens": [ + 50872, + 1282, + 262, + 6, + 377, + 7089, + 1462, + 1753, + 368, + 4666, + 21722, + 2680, + 635, + 9721, + 1531, + 287, + 6, + 996, + 7108, + 13, + 51058 + ], + "temperature": 0.0, + "avg_logprob": -0.6289185115269252, + "compression_ratio": 1.5749128919860627, + "no_speech_prob": 0.21948665380477905, + "confidence": 0.501, + "words": [ + { + "text": "On", + "start": 66.16, + "end": 67.08, + "confidence": 0.301 + }, + { + "text": "s'est", + "start": 67.08, + "end": 67.3, + "confidence": 0.561 + }, + { + "text": "espèrent", + "start": 67.3, + "end": 67.62, + "confidence": 0.134 + }, + { + "text": "de", + "start": 67.62, + "end": 67.66, + "confidence": 0.99 + }, + { + "text": "nous", + "start": 67.66, + "end": 67.84, + "confidence": 0.763 + }, + { + "text": "voter", + "start": 67.84, + "end": 68.36, + "confidence": 0.183 + }, + { + "text": "dans", + "start": 68.36, + "end": 68.86, + "confidence": 0.82 + }, + { + "text": "la", + "start": 68.86, + "end": 68.96, + "confidence": 0.614 + }, + { + "text": "relation", + "start": 68.96, + "end": 69.24, + "confidence": 0.949 + }, + { + "text": "à", + "start": 69.24, + "end": 69.42, + "confidence": 0.75 + }, + { + "text": "l'objet.", + "start": 69.42, + "end": 69.92, + "confidence": 0.887 + } + ] + }, + { + "id": 20, + "seek": 5596, + "start": 70.2, + "end": 71.22, + "text": " C'est facilement éterricion.", + "tokens": [ + 51058, + 383, + 6, + 377, + 23670, + 518, + 1136, + 391, + 1341, + 313, + 13, + 51122 + ], + "temperature": 0.0, + "avg_logprob": -0.6289185115269252, + "compression_ratio": 1.5749128919860627, + "no_speech_prob": 0.21948665380477905, + "confidence": 0.443, + "words": [ + { + "text": "C'est", + "start": 70.2, + "end": 70.34, + "confidence": 0.896 + }, + { + "text": "facilement", + "start": 70.34, + "end": 70.7, + "confidence": 0.566 + }, + { + "text": "éterricion.", + "start": 70.7, + "end": 71.22, + "confidence": 0.231 + } + ] + }, + { + "id": 21, + "seek": 5596, + "start": 71.64, + "end": 76.97, + "text": " Parce que la passion de l'utilisateur et ses affices a dépendance, cette objet d'un lieu", + "tokens": [ + 51122, + 20429, + 631, + 635, + 5418, + 368, + 287, + 6, + 20835, + 271, + 15540, + 1030, + 5385, + 2096, + 1473, + 257, + 45768, + 719, + 11, + 5550, + 14964, + 274, + 6, + 409, + 26036, + 51416 + ], + "temperature": 0.0, + "avg_logprob": -0.6289185115269252, + "compression_ratio": 1.5749128919860627, + "no_speech_prob": 0.21948665380477905, + "confidence": 0.457, + "words": [ + { + "text": "Parce", + "start": 71.64, + "end": 71.94, + "confidence": 0.68 + }, + { + "text": "que", + "start": 71.94, + "end": 72.32, + "confidence": 0.566 + }, + { + "text": "la", + "start": 72.32, + "end": 72.56, + "confidence": 0.333 + }, + { + "text": "passion", + "start": 72.56, + "end": 72.9, + "confidence": 0.266 + }, + { + "text": "de", + "start": 72.9, + "end": 73.26, + "confidence": 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qui rendent encore avec", + "tokens": [ + 51416, + 465, + 3887, + 11, + 2251, + 7089, + 30236, + 368, + 9721, + 368, + 42436, + 399, + 4163, + 476, + 10431, + 1956, + 6125, + 317, + 10122, + 4163, + 51671 + ], + "temperature": 0.0, + "avg_logprob": -0.6289185115269252, + "compression_ratio": 1.5749128919860627, + "no_speech_prob": 0.21948665380477905, + "confidence": 0.746, + "words": [ + { + "text": "en", + "start": 76.97, + "end": 77.2, + "confidence": 0.77 + }, + { + "text": "fait,", + "start": 77.2, + "end": 77.32, + "confidence": 0.944 + }, + { + "text": "une", + "start": 77.46, + "end": 77.48, + "confidence": 0.699 + }, + { + "text": "espèce", + "start": 77.48, + "end": 77.9, + "confidence": 0.97 + }, + { + "text": "de", + "start": 77.9, + "end": 78.08, + "confidence": 0.993 + }, + { + "text": "relation", + "start": 78.08, + "end": 78.5, + "confidence": 0.827 + }, + { + "text": "de", + "start": 78.5, + "end": 78.94, + "confidence": 0.714 + }, + { + "text": "médiation", + "start": 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j'ai l'impression comme ça que Nicolas se trompe pas vraiment.", + "tokens": [ + 51580, + 6313, + 361, + 6, + 1301, + 287, + 6, + 36107, + 5173, + 2788, + 631, + 38268, + 369, + 504, + 298, + 494, + 1736, + 8322, + 13, + 51738 + ], + "temperature": 0.0, + "avg_logprob": -0.45919205838401844, + "compression_ratio": 1.6159169550173011, + "no_speech_prob": 0.2066800743341446, + "confidence": 0.811, + "words": [ + { + "text": "Mais", + "start": 106.16, + "end": 106.5, + "confidence": 0.723 + }, + { + "text": "j'ai", + "start": 106.5, + "end": 106.92, + "confidence": 0.91 + }, + { + "text": "l'impression", + "start": 106.92, + "end": 107.34, + "confidence": 0.956 + }, + { + "text": "comme", + "start": 107.34, + "end": 107.58, + "confidence": 0.7 + }, + { + "text": "ça", + "start": 107.58, + "end": 107.74, + "confidence": 0.953 + }, + { + "text": "que", + "start": 107.74, + "end": 108.06, + "confidence": 0.941 + }, + { + "text": "Nicolas", + "start": 108.06, + "end": 108.46, + "confidence": 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plus n'était pas du même", + "tokens": [ + 50568, + 6313, + 11, + 635, + 27998, + 1288, + 297, + 6, + 9743, + 1736, + 1581, + 5698, + 6599, + 11, + 5926, + 476, + 319, + 7108, + 297, + 6, + 268, + 1804, + 297, + 6, + 9743, + 1736, + 1581, + 5698, + 50790 + ], + "temperature": 0.0, + "avg_logprob": -0.44286312419138135, + "compression_ratio": 1.7050847457627119, + "no_speech_prob": 0.14988036453723907, + "confidence": 0.702, + "words": [ + { + "text": "Mais,", + "start": 115.52, + "end": 115.82, + "confidence": 0.984 + }, + { + "text": "la", + "start": 115.92, + "end": 116.0, + "confidence": 0.961 + }, + { + "text": "dépense", + "start": 116.0, + "end": 116.42, + "confidence": 0.616 + }, + { + "text": "n'était", + "start": 116.42, + "end": 116.82, + "confidence": 0.956 + }, + { + "text": "pas", + "start": 116.82, + "end": 117.04, + "confidence": 0.994 + }, + { + "text": "du", + "start": 117.04, + "end": 117.2, + "confidence": 0.958 + }, + { + "text": "même", + "start": 117.2, + "end": 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"chaque", + "start": 135.32, + "end": 135.6, + "confidence": 0.99 + }, + { + "text": "soir", + "start": 135.6, + "end": 135.8, + "confidence": 0.997 + }, + { + "text": "pour", + "start": 135.8, + "end": 136.0, + "confidence": 0.981 + }, + { + "text": "discuter", + "start": 136.0, + "end": 136.34, + "confidence": 0.882 + }, + { + "text": "avec", + "start": 136.34, + "end": 136.5, + "confidence": 0.993 + }, + { + "text": "un", + "start": 136.5, + "end": 136.62, + "confidence": 0.967 + }, + { + "text": "copain.", + "start": 136.62, + "end": 137.04, + "confidence": 0.954 + } + ] + }, + { + "id": 41, + "seek": 13698, + "start": 137.32, + "end": 141.84, + "text": " Mais ça ne ressemble pas à ce qu'on peut ressentir à voir même mome aujourd'hui.", + "tokens": [ + 50376, + 6313, + 2788, + 408, + 725, + 37227, + 1736, + 1531, + 1769, + 421, + 6, + 266, + 5977, + 24689, + 317, + 347, + 1531, + 10695, + 5698, + 275, + 423, + 14023, + 6, + 10556, + 13, + 50606 + ], + "temperature": 0.0, + 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"text": "estimateur", + "start": 145.4, + "end": 145.86, + "confidence": 0.489 + } + ] + }, + { + "id": 43, + "seek": 13698, + "start": 145.96, + "end": 149.0, + "text": " extère de tomber de lâcher à l'éantrénée, ça m'a eu immédiate.", + "tokens": [ + 50810, + 1279, + 4212, + 368, + 2916, + 607, + 368, + 48835, + 6759, + 1531, + 287, + 6, + 526, + 394, + 81, + 3516, + 3856, + 11, + 2788, + 275, + 6, + 64, + 2228, + 3397, + 526, + 4504, + 473, + 13, + 50954 + ], + "temperature": 0.0, + "avg_logprob": -0.5335124224081806, + "compression_ratio": 1.6231454005934718, + "no_speech_prob": 0.10962729901075363, + "confidence": 0.415, + "words": [ + { + "text": "extère", + "start": 145.96, + "end": 146.4, + "confidence": 0.373 + }, + { + "text": "de", + "start": 146.4, + "end": 146.54, + "confidence": 0.254 + }, + { + "text": "tomber", + "start": 146.54, + "end": 146.7, + "confidence": 0.102 + }, + { + "text": "de", + "start": 146.7, + "end": 146.9, + "confidence": 0.455 + }, + { + "text": "lâcher", + "start": 146.9, + "end": 147.34, + "confidence": 0.751 + }, + { + "text": "à", + "start": 147.34, + "end": 147.46, + "confidence": 0.444 + }, + { + "text": "l'éantrénée,", + "start": 147.46, + "end": 147.9, + "confidence": 0.491 + }, + { + "text": "ça", + "start": 148.0, + "end": 148.02, + "confidence": 0.798 + }, + { + "text": "m'a", + "start": 148.02, + "end": 148.26, + "confidence": 0.529 + }, + { + "text": "eu", + "start": 148.26, + "end": 148.44, + "confidence": 0.136 + }, + { + "text": "immédiate.", + "start": 148.44, + "end": 149.0, + "confidence": 0.502 + } + ] + }, + { + "id": 44, + "seek": 13698, + "start": 149.08, + "end": 151.98, + "text": " Bon, je dis ça pour le mome, mais évidemment, va là, bon aussi.", + "tokens": [ + 50954, + 7368, + 11, + 1506, + 717, + 2788, + 2016, + 476, + 275, + 423, + 11, + 2420, + 24724, + 11, + 2773, + 3684, + 11, + 4428, + 6212, + 13, + 51126 + ], + "temperature": 0.0, + "avg_logprob": -0.5335124224081806, + "compression_ratio": 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"confidence": 0.591 + }, + { + "text": "bon", + "start": 151.6, + "end": 151.68, + "confidence": 0.827 + }, + { + "text": "aussi.", + "start": 151.68, + "end": 151.98, + "confidence": 0.163 + } + ] + }, + { + "id": 45, + "seek": 13698, + "start": 152.64, + "end": 154.64, + "text": " Donc, rapport immédiate d'accord.", + "tokens": [ + 51126, + 7477, + 11, + 18018, + 3397, + 526, + 4504, + 473, + 274, + 6, + 19947, + 13, + 51248 + ], + "temperature": 0.0, + "avg_logprob": -0.5335124224081806, + "compression_ratio": 1.6231454005934718, + "no_speech_prob": 0.10962729901075363, + "confidence": 0.86, + "words": [ + { + "text": "Donc,", + "start": 152.64, + "end": 153.08, + "confidence": 0.982 + }, + { + "text": "rapport", + "start": 153.16, + "end": 153.58, + "confidence": 0.979 + }, + { + "text": "immédiate", + "start": 153.58, + "end": 154.28, + "confidence": 0.839 + }, + { + "text": "d'accord.", + "start": 154.28, + "end": 154.64, + "confidence": 0.815 + } + ] + }, + { + "id": 46, + "seek": 13698, + "start": 155.66, + "end": 158.36, + "text": " Mais pourquoi, à ton impression qu'on en sortira, j'amé?", + "tokens": [ + 51248, + 6313, + 19934, + 11, + 1531, + 2952, + 9995, + 421, + 6, + 266, + 465, + 26906, + 64, + 11, + 361, + 6, + 335, + 526, + 30, + 51440 + ], + "temperature": 0.0, + "avg_logprob": -0.5335124224081806, + "compression_ratio": 1.6231454005934718, + "no_speech_prob": 0.10962729901075363, + "confidence": 0.709, + "words": [ + { + "text": "Mais", + "start": 155.66, + "end": 155.88, + "confidence": 0.984 + }, + { + "text": "pourquoi,", + "start": 155.88, + "end": 156.28, + "confidence": 0.898 + }, + { + "text": "à", + "start": 156.38, + "end": 156.58, + "confidence": 0.838 + }, + { + "text": "ton", + "start": 156.58, + "end": 156.7, + "confidence": 0.952 + }, + { + "text": "impression", + "start": 156.7, + "end": 157.06, + "confidence": 0.939 + }, + { + "text": "qu'on", + "start": 157.06, + "end": 157.28, + "confidence": 0.889 + }, + { + "text": "en", + "start": 157.28, + "end": 157.4, + "confidence": 0.801 + }, + { + "text": "sortira,", + "start": 157.4, + "end": 157.88, + "confidence": 0.577 + }, + { + "text": "j'amé?", + "start": 157.96, + "end": 158.36, + "confidence": 0.463 + } + ] + }, + { + "id": 47, + "seek": 13698, + "start": 159.16, + "end": 163.32, + "text": " Et puis, il faut en remettre la faute sur les gens qui ont créé cette critique merveilleux", + "tokens": [ + 51440, + 3790, + 9093, + 11, + 1930, + 8487, + 465, + 890, + 40681, + 635, + 2050, + 1169, + 1022, + 1512, + 10668, + 1956, + 6592, + 15609, + 526, + 5550, + 25673, + 3551, + 303, + 3409, + 2449, + 51678 + ], + "temperature": 0.0, + "avg_logprob": -0.5335124224081806, + "compression_ratio": 1.6231454005934718, + "no_speech_prob": 0.10962729901075363, + "confidence": 0.715, + "words": [ + { + "text": "Et", + "start": 159.16, + "end": 159.32, + "confidence": 0.83 + }, + { + "text": "puis,", + "start": 159.32, + "end": 159.46, + "confidence": 0.495 + }, + { + "text": "il", + "start": 159.62, + "end": 159.64, + "confidence": 0.594 + }, + { + "text": "faut", + "start": 159.64, + "end": 159.66, + "confidence": 0.951 + }, + { + "text": "en", + "start": 159.66, + "end": 159.78, + "confidence": 0.937 + }, + { + "text": "remettre", + "start": 159.78, + "end": 160.14, + "confidence": 0.984 + }, + { + "text": "la", + "start": 160.14, + "end": 160.42, + "confidence": 0.611 + }, + { + "text": "faute", + "start": 160.42, + "end": 160.68, + "confidence": 0.591 + }, + { + "text": "sur", + "start": 160.68, + "end": 160.98, + "confidence": 0.966 + }, + { + "text": "les", + "start": 160.98, + "end": 161.24, + "confidence": 0.83 + }, + { + "text": "gens", + "start": 161.24, + "end": 161.46, + "confidence": 0.987 + }, + { + "text": "qui", + "start": 161.46, + "end": 161.6, + "confidence": 0.98 + }, + { + "text": "ont", + "start": 161.6, + "end": 161.68, + "confidence": 0.951 + }, + { + "text": "créé", + "start": 161.68, + "end": 162.3, + "confidence": 0.95 + }, + { + "text": "cette", + "start": 162.3, + "end": 162.48, + "confidence": 0.909 + }, + { + "text": "critique", + "start": 162.48, + "end": 162.72, + "confidence": 0.033 + }, + { + "text": "merveilleux", + "start": 162.72, + "end": 163.32, + "confidence": 0.841 + } + ] + }, + { + "id": 48, + "seek": 13698, + "start": 163.32, + "end": 165.34, + "text": " et diabolique et diabolique par que merveilleux.", + "tokens": [ + 51678, + 1030, + 1026, + 14923, + 1925, + 1030, + 1026, + 14923, + 1925, + 971, + 631, + 3551, + 303, + 3409, + 2449, + 13, + 51778 + ], + "temperature": 0.0, + "avg_logprob": -0.5335124224081806, + "compression_ratio": 1.6231454005934718, + "no_speech_prob": 0.10962729901075363, + "confidence": 0.709, + "words": [ + { + "text": "et", + "start": 163.32, + "end": 163.44, + "confidence": 0.946 + }, + { + "text": "diabolique", + "start": 163.44, + "end": 163.86, + "confidence": 0.574 + }, + { + "text": "et", + "start": 163.86, + "end": 163.94, + "confidence": 0.239 + }, + { + "text": "diabolique", + "start": 163.94, + "end": 164.38, + "confidence": 0.893 + }, + { + "text": "par", + "start": 164.38, + "end": 164.62, + "confidence": 0.548 + }, + { + "text": "que", + "start": 164.62, + "end": 164.82, + "confidence": 0.529 + }, + { + "text": "merveilleux.", + "start": 164.82, + "end": 165.34, + "confidence": 0.981 + } + ] + }, + { + "id": 49, + "seek": 16526, + "start": 166.9, + "end": 168.8, + "text": " Les économistes parlent de dépendance du santé.", + "tokens": [ + 50410, + 6965, + 31171, + 22368, + 13734, + 317, + 368, + 45768, + 719, + 1581, + 30068, + 13, + 50542 + ], + "temperature": 0.0, + "avg_logprob": -0.6641062498092651, + "compression_ratio": 1.4761904761904763, + "no_speech_prob": 0.18914750218391418, + "confidence": 0.765, + "words": [ + { + "text": "Les", + "start": 166.9, + "end": 167.06, + "confidence": 0.699 + }, + { + "text": "économistes", + "start": 167.06, + "end": 167.52, + "confidence": 0.916 + }, + { + "text": "parlent", + "start": 167.52, + "end": 167.78, + "confidence": 0.794 + }, + { + "text": "de", + "start": 167.78, + "end": 167.84, + "confidence": 0.813 + }, + { + "text": "dépendance", + "start": 167.84, + "end": 168.36, + "confidence": 0.699 + }, + { + "text": "du", + "start": 168.36, + "end": 168.5, + "confidence": 0.963 + }, + { + "text": "santé.", + "start": 168.5, + "end": 168.8, + "confidence": 0.487 + } + ] + }, + { + "id": 50, + "seek": 16526, + "start": 168.82, + "end": 173.42, + "text": " Ces vidéos, en fait, on est un santé qui a été étabis, un soit mon termine, en marchand dessus,", + "tokens": [ + 50542, + 28414, + 25417, + 11, + 465, + 3887, + 11, + 322, + 871, + 517, + 30068, + 1956, + 257, + 8862, + 4823, + 455, + 271, + 11, + 517, + 12703, + 1108, + 1433, + 533, + 11, + 465, + 8368, + 474, + 30677, + 11, + 50784 + ], + "temperature": 0.0, + "avg_logprob": -0.6641062498092651, + "compression_ratio": 1.4761904761904763, + "no_speech_prob": 0.18914750218391418, + "confidence": 0.474, + "words": [ + { + "text": "Ces", + "start": 168.82, + "end": 169.14, + "confidence": 0.439 + }, + { + "text": "vidéos,", + "start": 169.14, + "end": 169.4, + "confidence": 0.459 + }, + { + "text": "en", + "start": 169.44, + "end": 169.64, + "confidence": 0.747 + }, + { + "text": "fait,", + "start": 169.64, + "end": 169.66, + "confidence": 0.976 + }, + { + "text": "on", + "start": 169.72, + "end": 169.74, + "confidence": 0.302 + }, + { + "text": "est", + "start": 169.74, + "end": 169.9, + "confidence": 0.815 + }, + { + "text": "un", + "start": 169.9, + "end": 170.48, + "confidence": 0.364 + }, + { + "text": "santé", + "start": 170.48, + "end": 170.8, + "confidence": 0.951 + }, + { + "text": "qui", + "start": 170.8, + "end": 170.92, + "confidence": 0.836 + }, + { + "text": "a", + "start": 170.92, + "end": 171.02, + "confidence": 0.821 + }, + { + "text": "été", + "start": 171.02, + "end": 171.12, + "confidence": 0.994 + }, + { + "text": "étabis,", + "start": 171.12, + "end": 171.5, + "confidence": 0.342 + }, + { + "text": "un", + "start": 171.76, + "end": 171.9, + "confidence": 0.233 + }, + { + "text": "soit", + "start": 171.9, + "end": 172.16, + "confidence": 0.311 + }, + { + "text": "mon", + "start": 172.16, + "end": 172.36, + "confidence": 0.205 + }, + { + "text": "termine,", + "start": 172.36, + "end": 172.72, + "confidence": 0.4 + }, + { + "text": "en", + "start": 172.8, + "end": 172.82, + "confidence": 0.31 + }, + { + "text": "marchand", + "start": 172.82, + "end": 173.14, + "confidence": 0.816 + }, + { + "text": "dessus,", + "start": 173.14, + "end": 173.42, + "confidence": 0.205 + } + ] + }, + { + "id": 51, + "seek": 16526, + "start": 173.86, + "end": 177.42, + "text": " soit des finissants débordes, des finissants, une signalétique.", + "tokens": [ + 50784, + 12703, + 730, + 962, + 891, + 1719, + 36529, + 765, + 279, + 11, + 730, + 962, + 891, + 1719, + 11, + 2251, + 6358, + 42379, + 13, + 50974 + ], + "temperature": 0.0, + "avg_logprob": -0.6641062498092651, + "compression_ratio": 1.4761904761904763, + "no_speech_prob": 0.18914750218391418, + "confidence": 0.582, + "words": [ + { + "text": "soit", + "start": 173.86, + "end": 174.4, + "confidence": 0.993 + }, + { + "text": "des", + "start": 174.4, + "end": 175.2, + "confidence": 0.762 + }, + { + "text": "finissants", + "start": 175.2, + "end": 175.58, + "confidence": 0.436 + }, + { + "text": "débordes,", + "start": 175.58, + "end": 175.98, + "confidence": 0.467 + }, + { + "text": "des", + "start": 176.14, + "end": 176.18, + "confidence": 0.22 + }, + { + "text": "finissants,", + "start": 176.18, + "end": 176.62, + "confidence": 0.961 + }, + { + "text": "une", + "start": 176.66, + "end": 176.84, + "confidence": 0.748 + }, + { + "text": "signalétique.", + "start": 176.84, + "end": 177.42, + "confidence": 0.567 + } + ] + } + ], + "language": "fr" +} \ No newline at end of file diff --git a/tests/expected/verbose.cpu/accurate.auto_bonjour_vous_allez_bien.mp3.stdout b/tests/expected/verbose.cpu/accurate.auto_bonjour_vous_allez_bien.mp3.stdout new file mode 100644 index 0000000000000000000000000000000000000000..532d5eaf637389f5cfdbecc58823d2ccd29cfacb --- /dev/null +++ b/tests/expected/verbose.cpu/accurate.auto_bonjour_vous_allez_bien.mp3.stdout @@ -0,0 +1,11 @@ +[00:00.460 --> 00:00.780] Боже +[00:00.780 --> 00:01.980] улыл! +[00:02.020 --> 00:02.260] Таков +[00:02.260 --> 00:02.400] уже +[00:02.400 --> 00:02.460] на +[00:02.460 --> 00:02.800] меня! +[00:32.980 --> 00:33.280] Боже +[00:33.280 --> 00:33.800] улыл! +[00:34.400 --> 00:34.800] Эскому +[00:34.800 --> 00:34.960] за +[00:34.960 --> 00:35.260] меня! diff --git a/tests/expected/verbose.cpu/accurate.fr_bonjour_vous_allez_bien.mp3.stdout b/tests/expected/verbose.cpu/accurate.fr_bonjour_vous_allez_bien.mp3.stdout new file mode 100644 index 0000000000000000000000000000000000000000..bbe59141c7bb85cc4567ff0ac51949b691aea753 --- /dev/null +++ b/tests/expected/verbose.cpu/accurate.fr_bonjour_vous_allez_bien.mp3.stdout @@ -0,0 +1,13 @@ +[00:00.460 --> 00:00.680] Bonjour! +[00:01.860 --> 00:02.140] Est-ce +[00:02.140 --> 00:02.180] que +[00:02.180 --> 00:02.340] vous +[00:02.340 --> 00:02.480] allez +[00:02.480 --> 00:02.800] bien? +[00:32.980 --> 00:33.160] Bonjour! +[00:34.400 --> 00:34.610] Bonjour! +[00:34.610 --> 00:34.660] Est-ce +[00:34.660 --> 00:34.720] que +[00:34.720 --> 00:34.860] vous +[00:34.860 --> 00:35.000] allez +[00:35.000 --> 00:35.340] bien? diff --git a/tests/expected/verbose.cpu/efficient.auto_bonjour_vous_allez_bien.mp3.stdout b/tests/expected/verbose.cpu/efficient.auto_bonjour_vous_allez_bien.mp3.stdout new file mode 100644 index 0000000000000000000000000000000000000000..532d5eaf637389f5cfdbecc58823d2ccd29cfacb --- /dev/null +++ b/tests/expected/verbose.cpu/efficient.auto_bonjour_vous_allez_bien.mp3.stdout @@ -0,0 +1,11 @@ +[00:00.460 --> 00:00.780] Боже +[00:00.780 --> 00:01.980] улыл! +[00:02.020 --> 00:02.260] Таков +[00:02.260 --> 00:02.400] уже +[00:02.400 --> 00:02.460] на +[00:02.460 --> 00:02.800] меня! +[00:32.980 --> 00:33.280] Боже +[00:33.280 --> 00:33.800] улыл! +[00:34.400 --> 00:34.800] Эскому +[00:34.800 --> 00:34.960] за +[00:34.960 --> 00:35.260] меня! diff --git a/tests/expected/verbose.cpu/efficient.fr_bonjour_vous_allez_bien.mp3.stdout b/tests/expected/verbose.cpu/efficient.fr_bonjour_vous_allez_bien.mp3.stdout new file mode 100644 index 0000000000000000000000000000000000000000..bbe59141c7bb85cc4567ff0ac51949b691aea753 --- /dev/null +++ b/tests/expected/verbose.cpu/efficient.fr_bonjour_vous_allez_bien.mp3.stdout @@ -0,0 +1,13 @@ +[00:00.460 --> 00:00.680] Bonjour! +[00:01.860 --> 00:02.140] Est-ce +[00:02.140 --> 00:02.180] que +[00:02.180 --> 00:02.340] vous +[00:02.340 --> 00:02.480] allez +[00:02.480 --> 00:02.800] bien? +[00:32.980 --> 00:33.160] Bonjour! +[00:34.400 --> 00:34.610] Bonjour! +[00:34.610 --> 00:34.660] Est-ce +[00:34.660 --> 00:34.720] que +[00:34.720 --> 00:34.860] vous +[00:34.860 --> 00:35.000] allez +[00:35.000 --> 00:35.340] bien? diff --git a/tests/expected/verbose.cpu/hf_bonjour.wav.stdout b/tests/expected/verbose.cpu/hf_bonjour.wav.stdout new file mode 100644 index 0000000000000000000000000000000000000000..99635535fd87302067c97ce13d42f2988dacdd83 --- /dev/null +++ b/tests/expected/verbose.cpu/hf_bonjour.wav.stdout @@ -0,0 +1,3 @@ +Detecting language using up to the first 30 seconds. Use `--language` to specify the language +Detected language: French +[00:00.120 --> 00:00.640] Bonjour. diff --git a/tests/expected/verbose/accurate.auto_bonjour_vous_allez_bien.mp3.stdout b/tests/expected/verbose/accurate.auto_bonjour_vous_allez_bien.mp3.stdout new file mode 100644 index 0000000000000000000000000000000000000000..6bfee4b97e33192bc46f69994bddcd817c220226 --- /dev/null +++ b/tests/expected/verbose/accurate.auto_bonjour_vous_allez_bien.mp3.stdout @@ -0,0 +1,10 @@ +Detecting language using up to the first 30 seconds. Use `--language` to specify the language +Detected language: Russian +[00:00.440 --> 00:00.860] Боже +[00:00.860 --> 00:01.880] улыл! +[00:01.880 --> 00:02.300] Эскому +[00:02.300 --> 00:03.140] зарегиан! +[00:32.980 --> 00:33.360] Боже +[00:33.360 --> 00:34.020] улыл! +[00:34.420 --> 00:34.840] Эскому +[00:34.840 --> 00:35.720] зарегиан! diff --git a/tests/expected/verbose/accurate.fr_bonjour_vous_allez_bien.mp3.stdout b/tests/expected/verbose/accurate.fr_bonjour_vous_allez_bien.mp3.stdout new file mode 100644 index 0000000000000000000000000000000000000000..ec0d882ef119c14b9da62584ee57728eab7691fd --- /dev/null +++ b/tests/expected/verbose/accurate.fr_bonjour_vous_allez_bien.mp3.stdout @@ -0,0 +1,11 @@ +[00:00.440 --> 00:01.440] Bonjour ! +[00:01.880 --> 00:02.200] Est-ce +[00:02.200 --> 00:02.240] que +[00:02.240 --> 00:02.360] vous +[00:02.360 --> 00:02.560] allez +[00:02.560 --> 00:03.120] bien ? +[00:32.980 --> 00:33.480] Bonjour ! +[00:34.420 --> 00:34.760] Esque +[00:34.760 --> 00:34.900] vous +[00:34.900 --> 00:35.080] allez +[00:35.080 --> 00:35.480] bien ! diff --git a/tests/expected/verbose/efficient.auto_bonjour_vous_allez_bien.mp3.stdout b/tests/expected/verbose/efficient.auto_bonjour_vous_allez_bien.mp3.stdout new file mode 100644 index 0000000000000000000000000000000000000000..6bfee4b97e33192bc46f69994bddcd817c220226 --- /dev/null +++ b/tests/expected/verbose/efficient.auto_bonjour_vous_allez_bien.mp3.stdout @@ -0,0 +1,10 @@ +Detecting language using up to the first 30 seconds. Use `--language` to specify the language +Detected language: Russian +[00:00.440 --> 00:00.860] Боже +[00:00.860 --> 00:01.880] улыл! +[00:01.880 --> 00:02.300] Эскому +[00:02.300 --> 00:03.140] зарегиан! +[00:32.980 --> 00:33.360] Боже +[00:33.360 --> 00:34.020] улыл! +[00:34.420 --> 00:34.840] Эскому +[00:34.840 --> 00:35.720] зарегиан! diff --git a/tests/expected/verbose/efficient.fr_bonjour_vous_allez_bien.mp3.stdout b/tests/expected/verbose/efficient.fr_bonjour_vous_allez_bien.mp3.stdout new file mode 100644 index 0000000000000000000000000000000000000000..ec0d882ef119c14b9da62584ee57728eab7691fd --- /dev/null +++ b/tests/expected/verbose/efficient.fr_bonjour_vous_allez_bien.mp3.stdout @@ -0,0 +1,11 @@ +[00:00.440 --> 00:01.440] Bonjour ! +[00:01.880 --> 00:02.200] Est-ce +[00:02.200 --> 00:02.240] que +[00:02.240 --> 00:02.360] vous +[00:02.360 --> 00:02.560] allez +[00:02.560 --> 00:03.120] bien ? +[00:32.980 --> 00:33.480] Bonjour ! +[00:34.420 --> 00:34.760] Esque +[00:34.760 --> 00:34.900] vous +[00:34.900 --> 00:35.080] allez +[00:35.080 --> 00:35.480] bien ! diff --git a/tests/expected/verbose/hf_bonjour.wav.stdout b/tests/expected/verbose/hf_bonjour.wav.stdout new file mode 100644 index 0000000000000000000000000000000000000000..99635535fd87302067c97ce13d42f2988dacdd83 --- /dev/null +++ b/tests/expected/verbose/hf_bonjour.wav.stdout @@ -0,0 +1,3 @@ +Detecting language using up to the first 30 seconds. Use `--language` to specify the language +Detected language: French +[00:00.120 --> 00:00.640] Bonjour. diff --git a/tests/expected/verbose/vad_auditok_words.wav.stdout b/tests/expected/verbose/vad_auditok_words.wav.stdout new file mode 100644 index 0000000000000000000000000000000000000000..9d3af7b842f6c5ec97a7c63f0b73168e966f7b98 --- /dev/null +++ b/tests/expected/verbose/vad_auditok_words.wav.stdout @@ -0,0 +1,8 @@ +[00:00.750 --> 00:01.470] settlement, +[00:02.950 --> 00:03.670] Kentucky, +[00:05.770 --> 00:06.290] causing +[00:07.900 --> 00:08.950] damage, +[00:10.900 --> 00:11.700] President, +[00:14.200 --> 00:14.780] expansion, +[00:17.120 --> 00:17.760] hospital, +[00:20.730 --> 00:21.290] devastated. diff --git a/tests/expected/verbose/vad_silero3.0_words.wav.stdout b/tests/expected/verbose/vad_silero3.0_words.wav.stdout new file mode 100644 index 0000000000000000000000000000000000000000..79e9f6107b1e48c0323c7fcfd843f9f3a9bf1be9 --- /dev/null +++ b/tests/expected/verbose/vad_silero3.0_words.wav.stdout @@ -0,0 +1,8 @@ +[00:00.760 --> 00:01.480] settlement, +[00:02.890 --> 00:03.670] Kentucky, +[00:05.710 --> 00:06.270] causing +[00:07.850 --> 00:08.930] damage, +[00:10.940 --> 00:11.700] president, +[00:14.200 --> 00:14.780] expansion, +[00:17.120 --> 00:17.780] hospital, +[00:20.140 --> 00:21.380] devastated. diff --git a/tests/expected/verbose/vad_silero3.1_words.wav.stdout b/tests/expected/verbose/vad_silero3.1_words.wav.stdout new file mode 100644 index 0000000000000000000000000000000000000000..54b0fd0716a5eed94c6a92c3ea372b879cec5401 --- /dev/null +++ b/tests/expected/verbose/vad_silero3.1_words.wav.stdout @@ -0,0 +1,8 @@ +[00:00.760 --> 00:01.480] settlement, +[00:02.920 --> 00:03.660] Kentucky, +[00:05.760 --> 00:06.260] causing +[00:07.850 --> 00:08.940] damage, +[00:10.840 --> 00:11.700] president, +[00:14.190 --> 00:14.770] expansion, +[00:17.130 --> 00:17.750] hospital, +[00:21.200 --> 00:21.380] devastated. diff --git a/tests/expected/verbose/vad_words.wav.stdout b/tests/expected/verbose/vad_words.wav.stdout new file mode 100644 index 0000000000000000000000000000000000000000..5dbf58fc48651f530a5a99a116062ab15fe66aeb --- /dev/null +++ b/tests/expected/verbose/vad_words.wav.stdout @@ -0,0 +1,8 @@ +[00:00.760 --> 00:01.460] settlement, +[00:02.900 --> 00:03.680] Kentucky, +[00:05.710 --> 00:06.270] causing +[00:07.890 --> 00:08.940] damage, +[00:10.930 --> 00:11.690] president, +[00:14.070 --> 00:14.770] expansion, +[00:17.140 --> 00:17.780] hospital, +[00:20.730 --> 00:21.370] devastated. diff --git a/tests/json_schema.json b/tests/json_schema.json new file mode 100644 index 0000000000000000000000000000000000000000..c3df000500227a0b937ac14f7f626414b978d77e --- /dev/null +++ b/tests/json_schema.json @@ -0,0 +1,146 @@ +{ + "type": "object", + "properties": { + "text": {"type": "string"}, + "segments": { + "type": "array", + "items": { + "type": "object", + "properties": { + "id": {"type": "integer", "minimum":0}, + "start": {"type": "number", "minimum":0}, + "end": {"type": "number", "minimum":0}, + "text": {"type": "string"}, + "tokens": { + "type": "array", + "items": {"type": "integer", "minimum": 0, "maximum": 51864} + }, + "temperature": {"type": "number", "minimum":0, "maximum":1}, + "avg_logprob": {"type": "number", "maximum":0}, + "compression_ratio": {"type": "number", "minimum":0}, + "no_speech_prob": {"type": "number", "minimum":0, "maximum":1}, + "confidence": {"type": "number", "minimum":0, "maximum":1}, + "words": { + "type": "array", + "items": { + "type": "object", + "properties": { + "text": {"type": "string"}, + "start": {"type": "number", "minimum":0}, + "end": {"type": "number", "minimum":0}, + "confidence": {"type": "number", "minimum":0, "maximum":1} + } + } + } + } + }, + "minItems": 0, + "uniqueItems": true + }, + "language": {"type": "string"}, + "language_probs": { + "type": "object", + "properties": { + "en": {"type": "number", "minimum":0, "maximum":1}, + "zh": {"type": "number", "minimum":0, "maximum":1}, + "de": {"type": "number", "minimum":0, "maximum":1}, + "es": {"type": "number", "minimum":0, "maximum":1}, + "ru": {"type": "number", "minimum":0, "maximum":1}, + "ko": {"type": "number", "minimum":0, "maximum":1}, + "fr": {"type": "number", "minimum":0, "maximum":1}, + "ja": {"type": "number", "minimum":0, "maximum":1}, + "pt": {"type": "number", "minimum":0, "maximum":1}, + "tr": {"type": "number", "minimum":0, "maximum":1}, + "pl": {"type": "number", "minimum":0, "maximum":1}, + "ca": {"type": "number", "minimum":0, "maximum":1}, + "nl": {"type": "number", "minimum":0, "maximum":1}, + "ar": {"type": "number", "minimum":0, "maximum":1}, + "sv": {"type": "number", "minimum":0, "maximum":1}, + "it": {"type": "number", "minimum":0, "maximum":1}, + "id": {"type": "number", "minimum":0, "maximum":1}, + "hi": {"type": "number", "minimum":0, "maximum":1}, + "fi": {"type": "number", "minimum":0, "maximum":1}, + "vi": {"type": "number", "minimum":0, "maximum":1}, + "he": {"type": "number", "minimum":0, "maximum":1}, + "uk": {"type": "number", "minimum":0, "maximum":1}, + "el": {"type": "number", "minimum":0, "maximum":1}, + "ms": {"type": "number", "minimum":0, "maximum":1}, + "cs": {"type": "number", "minimum":0, "maximum":1}, + "ro": {"type": "number", "minimum":0, "maximum":1}, + "da": {"type": "number", "minimum":0, "maximum":1}, + "hu": {"type": "number", "minimum":0, "maximum":1}, + "ta": {"type": "number", "minimum":0, "maximum":1}, + "no": {"type": "number", "minimum":0, "maximum":1}, + "th": {"type": "number", "minimum":0, "maximum":1}, + "ur": {"type": "number", "minimum":0, "maximum":1}, + "hr": {"type": "number", "minimum":0, "maximum":1}, + "bg": {"type": "number", "minimum":0, "maximum":1}, + "lt": {"type": "number", "minimum":0, "maximum":1}, + "la": {"type": "number", "minimum":0, "maximum":1}, + "mi": {"type": "number", "minimum":0, "maximum":1}, + "ml": {"type": "number", "minimum":0, "maximum":1}, + "cy": {"type": "number", "minimum":0, "maximum":1}, + "sk": {"type": "number", "minimum":0, "maximum":1}, + "te": {"type": "number", "minimum":0, "maximum":1}, + "fa": {"type": "number", "minimum":0, "maximum":1}, + "lv": {"type": "number", "minimum":0, "maximum":1}, + "bn": {"type": "number", "minimum":0, "maximum":1}, + "sr": {"type": "number", "minimum":0, "maximum":1}, + "az": {"type": "number", "minimum":0, "maximum":1}, + "sl": {"type": "number", "minimum":0, "maximum":1}, + "kn": {"type": "number", "minimum":0, "maximum":1}, + "et": {"type": "number", "minimum":0, "maximum":1}, + "mk": {"type": "number", "minimum":0, "maximum":1}, + "br": {"type": "number", "minimum":0, "maximum":1}, + "eu": {"type": "number", "minimum":0, "maximum":1}, + "is": {"type": "number", "minimum":0, "maximum":1}, + "hy": {"type": "number", "minimum":0, "maximum":1}, + "ne": {"type": "number", "minimum":0, "maximum":1}, + "mn": {"type": "number", "minimum":0, "maximum":1}, + "bs": {"type": "number", "minimum":0, "maximum":1}, + "kk": {"type": "number", "minimum":0, "maximum":1}, + "sq": {"type": "number", "minimum":0, "maximum":1}, + "sw": {"type": "number", "minimum":0, "maximum":1}, + "gl": {"type": "number", "minimum":0, "maximum":1}, + "mr": {"type": "number", "minimum":0, "maximum":1}, + "pa": {"type": "number", "minimum":0, "maximum":1}, + "si": {"type": "number", "minimum":0, "maximum":1}, + "km": {"type": "number", "minimum":0, "maximum":1}, + "sn": {"type": "number", "minimum":0, "maximum":1}, + "yo": {"type": "number", "minimum":0, "maximum":1}, + "so": {"type": "number", "minimum":0, "maximum":1}, + "af": {"type": "number", "minimum":0, "maximum":1}, + "oc": {"type": "number", "minimum":0, "maximum":1}, + "ka": {"type": "number", "minimum":0, "maximum":1}, + "be": {"type": "number", "minimum":0, "maximum":1}, + "tg": {"type": "number", "minimum":0, "maximum":1}, + "sd": {"type": "number", "minimum":0, "maximum":1}, + "gu": {"type": "number", "minimum":0, "maximum":1}, + "am": {"type": "number", "minimum":0, "maximum":1}, + "yi": {"type": "number", "minimum":0, "maximum":1}, + "lo": {"type": "number", "minimum":0, "maximum":1}, + "uz": {"type": "number", "minimum":0, "maximum":1}, + "fo": {"type": "number", "minimum":0, "maximum":1}, + "ht": {"type": "number", "minimum":0, "maximum":1}, + "ps": {"type": "number", "minimum":0, "maximum":1}, + "tk": {"type": "number", "minimum":0, "maximum":1}, + "nn": {"type": "number", "minimum":0, "maximum":1}, + "mt": {"type": "number", "minimum":0, "maximum":1}, + "sa": {"type": "number", "minimum":0, "maximum":1}, + "lb": {"type": "number", "minimum":0, "maximum":1}, + "my": {"type": "number", "minimum":0, "maximum":1}, + "bo": {"type": "number", "minimum":0, "maximum":1}, + "tl": {"type": "number", "minimum":0, "maximum":1}, + "mg": {"type": "number", "minimum":0, "maximum":1}, + "as": {"type": "number", "minimum":0, "maximum":1}, + "tt": {"type": "number", "minimum":0, "maximum":1}, + "haw": {"type": "number", "minimum":0, "maximum":1}, + "ln": {"type": "number", "minimum":0, "maximum":1}, + "ha": {"type": "number", "minimum":0, "maximum":1}, + "ba": {"type": "number", "minimum":0, "maximum":1}, + "jw": {"type": "number", "minimum":0, "maximum":1}, + "su": {"type": "number", "minimum":0, "maximum":1} + } + } + } +} diff --git a/tests/run_tests.py b/tests/run_tests.py new file mode 100644 index 0000000000000000000000000000000000000000..0b202b69af065c478fc99607b012ccec40cf5580 --- /dev/null +++ b/tests/run_tests.py @@ -0,0 +1,48 @@ +import sys +import unittest + +from test_transcribe import * +import test_transcribe + +if __name__ == '__main__': + + # Handle several ways of generating expected outputs + if "--long" in sys.argv: + test_transcribe.SKIP_LONG_TEST_IF_CPU = False + sys.argv.remove("--long") + if "--generate" in sys.argv: + test_transcribe.FAIL_IF_REFERENCE_NOT_FOUND = False + sys.argv.remove("--generate") + if "--generate_device" in sys.argv: + test_transcribe.GENERATE_DEVICE_DEPENDENT = True + test_transcribe.FAIL_IF_REFERENCE_NOT_FOUND = False + sys.argv.remove("--generate_device") + if "--generate_new" in sys.argv: + test_transcribe.GENERATE_NEW_ONLY = True + test_transcribe.FAIL_IF_REFERENCE_NOT_FOUND = False + sys.argv.remove("--generate_new") + if "--generate_all" in sys.argv: + test_transcribe.GENERATE_ALL = True + test_transcribe.FAIL_IF_REFERENCE_NOT_FOUND = False + sys.argv.remove("--generate_all") + + # Pass options to whisper_timestamped CLI + args = sys.argv[1:] + for i, arg in enumerate(args): + if arg not in [ + "-h", "--help", + "-v", "--verbose", + "--locals", + "-q", "--quiet", + "-f", "--failfast", + "-c", "--catch", + "-b", "--buffer", + "-k", + ] \ + and not arg.startswith("Test") \ + and (i==0 or args[i-1] not in ["-k"]) \ + and (arg.startswith("-") or (i>0 and args[i-1].startswith("-"))): + test_transcribe.CMD_OPTIONS.append(arg) + sys.argv.remove(arg) + + unittest.main() diff --git a/tests/test_transcribe.py b/tests/test_transcribe.py new file mode 100644 index 0000000000000000000000000000000000000000..fc5643c3e9e0ddfb415d544c9a71c4b8ad315198 --- /dev/null +++ b/tests/test_transcribe.py @@ -0,0 +1,902 @@ +__author__ = "Jérôme Louradour" +__credits__ = ["Jérôme Louradour"] +__license__ = "GPLv3" + +import unittest +import sys +import os +import subprocess +import shutil +import tempfile +import json +import torch +import jsonschema + +FAIL_IF_REFERENCE_NOT_FOUND = True +GENERATE_NEW_ONLY = False +GENERATE_ALL = False +GENERATE_DEVICE_DEPENDENT = False +SKIP_LONG_TEST_IF_CPU = True +CMD_OPTIONS = [] + + +class TestHelper(unittest.TestCase): + + def skipLongTests(self): + return SKIP_LONG_TEST_IF_CPU and not torch.cuda.is_available() + + def setUp(self): + self.maxDiff = None + self.createdReferences = [] + + def tearDown(self): + if GENERATE_ALL or GENERATE_NEW_ONLY or not FAIL_IF_REFERENCE_NOT_FOUND or GENERATE_DEVICE_DEPENDENT: + if len(self.createdReferences) > 0: + print("WARNING: Created references: " + + ", ".join(self.createdReferences).replace(self.get_data_path()+"/", "")) + else: + self.assertEqual(self.createdReferences, [], "Created references: " + + ", ".join(self.createdReferences).replace(self.get_data_path()+"/", "")) + + def get_main_path(self, fn=None, check=False): + return self._get_path("whisper_timestamped", fn, check=check) + + def get_output_path(self, fn=None): + if fn == None: + return tempfile.gettempdir() + return os.path.join(tempfile.gettempdir(), fn + self._extra_cmd_options()) + + def get_expected_path(self, fn=None, check=False): + return self._get_path("tests/expected" + self._extra_cmd_options(), fn, check=check) + + def _extra_cmd_options(self): + s = "".join([f.replace("-","").strip() for f in CMD_OPTIONS]) + if s: + return "." + s + return "" + + def get_data_files(self, files=None, excluded_by_default=["apollo11.mp3", "music.mp4", "arabic.mp3", "japanese.mp3", "empty.wav", "words.wav"]): + if files == None: + files = os.listdir(self.get_data_path()) + files = [f for f in files if f not in excluded_by_default and not f.endswith("json")] + files = sorted(files) + return [self.get_data_path(fn) for fn in files] + + def get_generated_files(self, input_filename, output_path, extensions): + for ext in extensions: + yield os.path.join(output_path, os.path.basename(input_filename) + "." + ext.lstrip(".")) + + def main_script(self, pyscript = "transcribe.py", exename = "whisper_timestamped"): + main_script = self.get_main_path(pyscript, check=False) + if not os.path.exists(main_script): + main_script = exename + return main_script + + def assertRun(self, cmd): + if isinstance(cmd, str): + return self.assertRun(cmd.split()) + curdir = os.getcwd() + os.chdir(tempfile.gettempdir()) + if cmd[0].endswith(".py"): + cmd = [sys.executable] + cmd + print("Running:", " ".join(cmd)) + p = subprocess.Popen(cmd, + # Otherwise ".local" path might be missing + env=dict( + os.environ, PYTHONPATH=os.pathsep.join(sys.path)), + stdout=subprocess.PIPE, stderr=subprocess.PIPE + ) + os.chdir(curdir) + (stdout, stderr) = p.communicate() + self.assertEqual(p.returncode, 0, msg=stderr.decode("utf-8")) + return (stdout.decode("utf-8"), stderr.decode("utf-8")) + + def assertNonRegression(self, content, reference, string_is_file=True): + """ + Check that a file/folder is the same as a reference file/folder. + """ + if isinstance(content, dict): + # Make a temporary file + with tempfile.NamedTemporaryFile(mode="w", suffix=".json", encoding="utf8", delete=False) as f: + json.dump(content, f, indent=2, ensure_ascii=False) + content = f.name + res = self.assertNonRegression(f.name, reference) + os.remove(f.name) + return res + elif not isinstance(content, str): + raise ValueError(f"Invalid content type: {type(content)}") + + if not string_is_file: + with tempfile.NamedTemporaryFile(mode="w", suffix=".txt", encoding="utf8", delete=False) as f: + f.write(content) + content = f.name + res = self.assertNonRegression(f.name, reference) + os.remove(f.name) + return res + + self.assertTrue(os.path.exists(content), f"Missing file: {content}") + is_file = os.path.isfile(reference) if os.path.exists(reference) else os.path.isfile(content) + + reference = self.get_expected_path( + reference, check=FAIL_IF_REFERENCE_NOT_FOUND) + if not os.path.exists(reference) or ((GENERATE_ALL or GENERATE_DEVICE_DEPENDENT) and reference not in self.createdReferences): + dirname = os.path.dirname(reference) + if not os.path.isdir(dirname): + os.makedirs(dirname) + if is_file: + shutil.copyfile(content, reference) + else: + shutil.copytree(content, reference) + self.createdReferences.append(reference) + + if is_file: + self.assertTrue(os.path.isfile(content)) + self._check_file_non_regression(content, reference) + else: + self.assertTrue(os.path.isdir(content)) + for root, dirs, files in os.walk(content): + for f in files: + f_ref = os.path.join(reference, f) + self.assertTrue(os.path.isfile(f_ref), + f"Additional file: {f}") + self._check_file_non_regression( + os.path.join(root, f), f_ref) + for root, dirs, files in os.walk(reference): + for f in files: + f = os.path.join(content, f) + self.assertTrue(os.path.isfile(f), f"Missing file: {f}") + + def get_data_path(self, fn=None, check=True): + return self._get_path("tests/data", fn, check) + + def _get_path(self, prefix, fn=None, check=True): + path = os.path.join( + os.path.dirname(os.path.dirname(__file__)), + prefix + ) + if fn: + path = os.path.join(path, fn) + if check: + self.assertTrue(os.path.exists(path), f"Cannot find {path}") + return path + + def _check_file_non_regression(self, file, reference): + if file.endswith(".json"): + with open(file) as f: + content = json.load(f) + with open(reference) as f: + reference_content = json.load(f) + if "language" in content and "language" in reference_content: + content["language"] = self.norm_language(content["language"]) + reference_content["language"] = self.norm_language(reference_content["language"]) + self.assertClose(content, reference_content, + msg=f"File {file} does not match reference {reference}") + return + with open(file) as f: + content = f.readlines() + with open(reference) as f: + reference_content = f.readlines() + self.assertEqual(content, reference_content, + msg=f"File {file} does not match reference {reference}") + + def assertClose(self, obj1, obj2, msg=None): + return self.assertEqual(self.loose(obj1), self.loose(obj2), msg=msg) + + def loose(self, obj): + # Return an approximative value of an object + if isinstance(obj, list): + return [self.loose(a) for a in obj] + if isinstance(obj, float): + f = round(obj, 1) + return 0.0 if f == -0.0 else f + if isinstance(obj, dict): + return {k: self.loose(v) for k, v in obj.items()} + if isinstance(obj, tuple): + return tuple(self.loose(list(obj))) + if isinstance(obj, set): + return self.loose(list(obj), "set") + return obj + + def get_audio_duration(self, audio_file): + # Get the duration in sec *without introducing additional dependencies* + import whisper + return len(whisper.load_audio(audio_file)) / whisper.audio.SAMPLE_RATE + + def get_device_str(self): + import torch + return "cpu" if not torch.cuda.is_available() else "cuda" + + def norm_language(self, language): + # Cheap custom stuff to avoid importing everything + return { + "japanese": "ja", + }.get(language.lower(), language) + + +class TestHelperCli(TestHelper): + + json_schema = None + + def _test_cli_(self, opts, name, files=None, extensions=["words.json"], prefix=None, one_per_call=True, device_specific=None): + """ + Test command line + opts: list of options + name: name of the test + files: list of files to process + extensions: list of extensions to check, or None to test the stdout + prefix: prefix to add to the reference files + one_per_call: if True, each file is processed separately, otherwise all files are processed by a single process + """ + + opts = opts + CMD_OPTIONS + + output_dir = self.get_output_path(name) + + input_filenames = self.get_data_files(files) + + for i, input_filename in enumerate(input_filenames): + + # Butterfly effect: Results are different depending on the device for long files + duration = self.get_audio_duration(input_filename) + if device_specific is None: + device_dependent = duration > 60 or (duration > 30 and "tiny_fr" in name) or ("empty" in input_filename and "medium_auto" in name) + else: + device_dependent = device_specific + name_ = name + if device_dependent and self.get_device_str() != "cuda": + name_ += f".{self.get_device_str()}" + + def ref_name(output_filename): + return name_ + "/" + (f"{prefix}_" if prefix else "") + os.path.basename(output_filename) + generic_name = ref_name(input_filename + ".*") + + if GENERATE_DEVICE_DEPENDENT and not device_dependent: + print("Skipping non-regression test", generic_name) + continue + + if GENERATE_NEW_ONLY and min([os.path.exists(self.get_expected_path(ref_name(output_filename))) + for output_filename in self.get_generated_files(input_filename, output_dir, extensions=extensions)] + ): + print("Skipping non-regression test", generic_name) + continue + + print("Running non-regression test", generic_name) + + if one_per_call or i == 0: + if one_per_call: + (stdout, stderr) = self.assertRun([self.main_script(), input_filename, "--output_dir", output_dir, *opts]) + else: + (stdout, stderr) = self.assertRun([self.main_script(), *input_filenames, "--output_dir", output_dir, *opts]) + print(stdout) + print(stderr) + + output_json = self.get_generated_files(input_filename, output_dir, extensions=["words.json"]).__next__() + if os.path.isfile(output_json): + self.check_json(output_json) + + if extensions is None: + output_filename = list(self.get_generated_files(input_filename, output_dir, extensions=["stdout"]))[0] + self.assertNonRegression(stdout, ref_name(output_filename), string_is_file=False) + else: + for output_filename in self.get_generated_files(input_filename, output_dir, extensions=extensions): + self.assertNonRegression(output_filename, ref_name(output_filename)) + + + shutil.rmtree(output_dir, ignore_errors=True) + + def check_json(self, json_file): + with open(json_file) as f: + content = json.load(f) + + if self.json_schema is None: + schema_file = os.path.join(os.path.dirname(__file__), "json_schema.json") + self.assertTrue(os.path.isfile(schema_file), msg=f"Schema file {schema_file} not found") + self.json_schema = json.load(open(schema_file)) + + jsonschema.validate(instance=content, schema=self.json_schema) + + + +class TestTranscribeTiny(TestHelperCli): + + def test_cli_tiny_auto(self): + self._test_cli_( + ["--model", "tiny"], + "tiny_auto", + ) + + def test_cli_tiny_fr(self): + self._test_cli_( + ["--model", "tiny", "--language", "fr"], + "tiny_fr", + ) + + +class TestTranscribeMedium(TestHelperCli): + + def test_cli_medium_auto(self): + self._test_cli_( + ["--model", "medium"], + "medium_auto", + ) + + def test_cli_medium_fr(self): + self._test_cli_( + ["--model", "medium", "--language", "fr"], + "medium_fr", + ) + + +class TestTranscribeNaive(TestHelperCli): + + def test_naive(self): + + self._test_cli_( + ["--model", "small", "--language", "en", "--efficient", "--naive"], + "naive", + files=["apollo11.mp3"], + prefix="naive", + ) + + self._test_cli_( + ["--model", "small", "--language", "en", "--accurate"], + "naive", + files=["apollo11.mp3"], + prefix="accurate", + ) + + def test_stucked_segments(self): + self._test_cli_( + ["--model", "tiny"], + "corner_cases", + files=["apollo11.mp3"], + prefix="accurate.tiny", + ) + + +class TestTranscribeCornerCases(TestHelperCli): + + def test_stucked_lm(self): + if self.skipLongTests(): + return + + self._test_cli_( + ["--model", "small", "--language", "en", "--efficient"], + "corner_cases", + files=["apollo11.mp3"], + prefix="stucked_lm", + ) + + def test_punctuation_only(self): + + # When there is only a punctuation detected in a segment, it could cause issue #24 + self._test_cli_( + ["--model", "medium.en", "--efficient", "--punctuations", "False"], + "corner_cases", + files=["empty.wav"], + prefix="issue24", + ) + + def test_temperature(self): + + self._test_cli_( + ["--model", "small", "--language", "English", + "--condition", "False", "--temperature", "0.1", "--efficient"], + "corner_cases", + files=["apollo11.mp3"], + prefix="random.nocond", + ) + + if self.skipLongTests(): + return + + self._test_cli_( + ["--model", "small", "--language", "en", "--temperature", "0.2", "--efficient"], + "corner_cases", + files=["apollo11.mp3"], + prefix="random", + ) + + def test_not_conditioned(self): + + if not os.path.exists(self.get_data_path("music.mp4", check=False)): + return + if self.skipLongTests(): + return + + self._test_cli_( + ["--model", "medium", "--language", "en", "--condition", "False", "--efficient"], + "corner_cases", + files=["music.mp4"], + prefix="nocond", + ) + + self._test_cli_( + ["--model", "medium", "--language", "en", + "--condition", "False", "--temperature", "0.4", "--efficient"], + "corner_cases", + files=["music.mp4"], + prefix="nocond.random", + ) + + def test_large(self): + if self.skipLongTests(): + return + + self._test_cli_( + ["--model", "large-v2", "--language", "en", + "--condition", "False", "--temperature", "0.4", "--efficient"], + "corner_cases", + files=["apollo11.mp3"], + prefix="large", + ) + + if os.path.exists(self.get_data_path("arabic.mp3", check=False)): + self._test_cli_( + ["--model", "large-v2", "--language", "Arabic", "--efficient"], + "corner_cases", + files=["arabic.mp3"] + ) + + def test_gloria(self): + + for model in ["medium", "large-v2"]: + for dec in ["efficient", "accurate"]: + self._test_cli_( + ["--model", model, "--language", "en", "--" + dec], + "corner_cases", + files=["gloria.mp3"], + prefix=model + "." + dec, + ) + +class TestTranscribeMonolingual(TestHelperCli): + + def test_monolingual_tiny(self): + + files = ["bonjour_vous_allez_bien.mp3"] + + self._test_cli_( + ["--model", "tiny.en", "--efficient"], + "tiny.en", + files=files, + prefix="efficient", + ) + + self._test_cli_( + ["--model", "tiny.en", "--accurate"], + "tiny.en", + files=files, + prefix="accurate", + ) + + self._test_cli_( + ["--model", "tiny.en", "--condition", "False", "--efficient"], + "tiny.en", + files=files, + prefix="nocond", + ) + + def test_monolingual_small(self): + + if os.path.exists(self.get_data_path("arabic.mp3", check=False)): + self._test_cli_( + ["--model", "small.en", "--condition", "True", "--efficient"], + "small.en", + files=["arabic.mp3"], + device_specific=True, + ) + + +class TestTranscribeWithVad(TestHelperCli): + + def test_vad_default(self): + self._test_cli_( + ["--model", "tiny", "--accurate", "--language", "en", "--vad", "True", "--verbose", "True"], + "verbose", + files=["words.wav"], + prefix="vad", + extensions=None, + ) + + def test_vad_custom_silero(self): + self._test_cli_( + ["--model", "tiny", "--accurate", "--language", "en", "--vad", "silero:v3.1", "--verbose", "True"], + "verbose", + files=["words.wav"], + prefix="vad_silero3.1", + extensions=None, + ) + self._test_cli_( + ["--model", "tiny", "--accurate", "--language", "en", "--vad", "silero:v3.0", "--verbose", "True"], + "verbose", + files=["words.wav"], + prefix="vad_silero3.0", + extensions=None, + ) + + def test_vad_custom_auditok(self): + self._test_cli_( + ["--model", "tiny", "--language", "en", "--vad", "auditok", "--verbose", "True"], + "verbose", + files=["words.wav"], + prefix="vad_auditok", + extensions=None, + ) + + +class TestTranscribeUnspacedLanguage(TestHelperCli): + + def test_japanese(self): + + self._test_cli_( + ["--model", "tiny", "--efficient"], + "tiny_auto", + files=["japanese.mp3"], + device_specific=True, + ) + + self._test_cli_( + ["--model", "tiny", "--language", "Japanese", "--efficient"], + "tiny_auto", + files=["japanese.mp3"], + prefix="jp", + device_specific=True, + ) + + self._test_cli_( + ["--model", "tiny", "--accurate"], + "tiny_auto", + files=["japanese.mp3"], + prefix="accurate", + device_specific=True, + ) + + self._test_cli_( + ["--model", "tiny", "--language", "Japanese", "--accurate"], + "tiny_auto", + files=["japanese.mp3"], + prefix="accurate_jp", + device_specific=True, + ) + +class TestTranscribeFormats(TestHelperCli): + + def test_cli_outputs(self): + files = ["punctuations.mp3", "bonjour.wav"] + extensions = ["txt", "srt", "vtt", "words.srt", "words.vtt", + "words.json", "csv", "words.csv", "tsv", "words.tsv"] + opts = ["--model", "medium", "--language", "fr"] + + # An audio / model combination that produces coma + self._test_cli_( + opts, + "punctuations_yes", + files=files, + extensions=extensions, + one_per_call=False, + ) + self._test_cli_( + opts + ["--punctuations", "False"], + "punctuations_no", + files=files, + extensions=extensions, + one_per_call=False, + ) + + def test_verbose(self): + + files = ["bonjour_vous_allez_bien.mp3"] + opts = ["--model", "tiny", "--verbose", "True"] + + self._test_cli_( + ["--efficient", *opts], + "verbose", files=files, extensions=None, + prefix="efficient.auto", + device_specific=True, + ) + + self._test_cli_( + ["--language", "fr", "--efficient", *opts], + "verbose", files=files, extensions=None, + prefix="efficient.fr", + device_specific=True, + ) + + self._test_cli_( + opts, + "verbose", files=files, extensions=None, + prefix="accurate.auto", + device_specific=True, + ) + + self._test_cli_( + ["--language", "fr", *opts], + "verbose", files=files, extensions=None, + prefix="accurate.fr", + device_specific=True, + ) + +class TestMakeSubtitles(TestHelper): + + def test_make_subtitles(self): + + main_script = self.main_script("make_subtitles.py", "whisper_timestamped_make_subtitles") + + inputs = [ + self.get_data_path("smartphone.mp3.words.json"), + self.get_data_path("no_punctuations.mp3.words.json", check=True), + self.get_data_path("yes_punctuations.mp3.words.json", check=True), + ] + + for i, input in enumerate(inputs): + filename = os.path.basename(input).replace(".words.json", "") + for len in 6, 20, 50: + output_dir = self.get_output_path() + self.assertRun([main_script, + input if i > 0 else self.get_data_path(), output_dir, + "--max_length", str(len), + ]) + for format in "vtt", "srt",: + output_file = os.path.join(output_dir, f"{filename}.{format}") + self.assertTrue(os.path.isfile(output_file), msg=f"File {output_file} not found") + expected_file = f"split_subtitles/{filename.split('_')[-1]}_{len}.{format}" + self.assertNonRegression(output_file, expected_file) + os.remove(output_file) + self.assertRun([main_script, + input, output_file, + "--max_length", str(len), + ]) + self.assertTrue(os.path.isfile(output_file), msg=f"File {output_file} not found") + self.assertNonRegression(output_file, expected_file) + +class TestHuggingFaceModel(TestHelperCli): + + def test_hugging_face_model(self): + + self._test_cli_( + ["--model", "qanastek/whisper-tiny-french-cased", "--verbose", "True"], + "verbose", files=["bonjour.wav"], extensions=None, + prefix="hf", + device_specific=True, + ) + + import tempfile + from transformers import WhisperForConditionalGeneration, WhisperProcessor, GenerationConfig + tempfolder = os.path.join(tempfile.gettempdir(), "tmp_whisper-tiny-french-cased") + + for safe_serialization in False, True,: + for max_shard_size in "100MB", "10GB", : + shutil.rmtree(tempfolder, ignore_errors=True) + model = WhisperForConditionalGeneration.from_pretrained("qanastek/whisper-tiny-french-cased") + processor = WhisperProcessor.from_pretrained("qanastek/whisper-tiny-french-cased") + try: + model.save_pretrained(tempfolder, safe_serialization=safe_serialization, max_shard_size=max_shard_size) + processor.save_pretrained(tempfolder) + self._test_cli_( + ["--model", tempfolder, "--verbose", "True"], + "verbose", files=["bonjour.wav"], extensions=None, + prefix="hf", + device_specific=True, + ) + finally: + shutil.rmtree(tempfolder) + + +# "ZZZ" to run this test at last (because it will fill the CUDA with some memory) +class TestZZZPythonImport(TestHelper): + + def test_python_import(self): + + try: + import whisper_timestamped + except ModuleNotFoundError: + sys.path.append(os.path.realpath( + os.path.dirname(os.path.dirname(__file__)))) + import whisper_timestamped + + # Test version + version = whisper_timestamped.__version__ + self.assertTrue(isinstance(version, str)) + + (stdout, sterr) = self.assertRun([self.main_script(), "-v"]) + self.assertEqual(stdout.strip(), version) + + model = whisper_timestamped.load_model("tiny") + + # Check processing of different files + for filename in "bonjour.wav", "laugh1.mp3", "laugh2.mp3": + res = whisper_timestamped.transcribe( + model, self.get_data_path(filename)) + if self._can_generate_reference(): + self.assertNonRegression(res, f"tiny_auto/{filename}.words.json") + + for filename in "bonjour.wav", "laugh1.mp3", "laugh2.mp3": + res = whisper_timestamped.transcribe( + model, self.get_data_path(filename), language="fr") + if self._can_generate_reference(): + self.assertNonRegression(res, f"tiny_fr/{filename}.words.json") + + def _can_generate_reference(self): + return not GENERATE_DEVICE_DEPENDENT or self.get_device_str() != "cpu" + + def test_split_tokens(self): + + import whisper + whisperversion = whisper.__version__ + + import whisper_timestamped as whisper + from whisper_timestamped.transcribe import split_tokens_on_spaces + + tokenizer = whisper.tokenizer.get_tokenizer(True, language=None) + + # 220 means space + tokens = [50364, 220, 6455, 11, 2232, 11, 286, 2041, 11, 2232, 11, 8660, + 291, 808, 493, 220, 365, 11, 220, 445, 718, 505, 458, 13, 220, 50714] + + self.assertEqual( + split_tokens_on_spaces(tokens, tokenizer), + (['<|0.00|>', 'So,', 'uh,', 'I', 'guess,', 'uh,', 'wherever', 'you', 'come', 'up', 'with,', 'just', 'let', 'us', 'know.', '<|7.00|>'], + [['<|0.00|>'], + [' ', 'So', ','], + [' uh', ','], + [' I'], + [' guess', ','], + [' uh', ','], + [' wherever'], + [' you'], + [' come'], + [' up'], + [' ', ' with', ','], + [' ', ' just'], + [' let'], + [' us'], + [' know', '.', ' '], + ['<|7.00|>']], + [[50364], + [220, 6455, 11], + [2232, 11], + [286], + [2041, 11], + [2232, 11], + [8660], + [291], + [808], + [493], + [220, 365, 11], + [220, 445], + [718], + [505], + [458, 13, 220], + [50714] + ]) + ) + + tokens = [50366, 314, 6, 11771, 17134, 11, 4666, 11, 1022, 220, 875, 2557, 68, 11, 6992, 631, 269, 6, 377, 220, 409, 7282, 1956, 871, 566, 2707, 394, 1956, 256, 622, 8208, 631, 8208, 871, 517, 7282, 1956, 5977, 7418, 371, 1004, 306, 580, 11, 5977, 12, 9498, 9505, 84, 6, 50416] + self.assertEqual( + split_tokens_on_spaces(tokens, tokenizer), + ( + ['<|0.04|>', "T'façon,", 'nous,', 'sur', 'la', 'touche,', 'parce', 'que', "c'est", 'un', 'sport', 'qui', 'est', 'important', 'qui', 'tue', 'deux', 'que', 'deux', 'est', 'un', 'sport', 'qui', 'peut', 'être', 'violent,', 'peut-être', "qu'", '<|1.04|>'], + [['<|0.04|>'], + [' T', "'", 'fa', 'çon', ','], + [' nous', ','], + [' sur'], + [' ', 'la'], + [' touch', 'e', ','], + [' parce'], + [' que'], + [' c', "'", 'est'], + [' ', 'un'], + [' sport'], + [' qui'], + [' est'], + [' im', 'port', 'ant'], + [' qui'], + [' t', 'ue'], + [' deux'], + [' que'], + [' deux'], + [' est'], + [' un'], + [' sport'], + [' qui'], + [' peut'], + [' être'], + [' v', 'io', 'le', 'nt', ','], + [' peut', '-', 'être'], + [' q', 'u', "'"], + ['<|1.04|>']], + [[50366], + [314, 6, 11771, 17134, 11], + [4666, 11], + [1022], + [220, 875], + [2557, 68, 11], + [6992], + [631], + [269, 6, 377], + [220, 409], + [7282], + [1956], + [871], + [566, 2707, 394], + [1956], + [256, 622], + [8208], + [631], + [8208], + [871], + [517], + [7282], + [1956], + [5977], + [7418], + [371, 1004, 306, 580, 11], + [5977, 12, 9498], + [9505, 84, 6], + [50416]] + ) + ) + + tokens = [50364, 220, 220, 6455, 11, 220, 220, 2232, 220, 220, 11, 220, 50714] + self.assertEqual( + split_tokens_on_spaces(tokens, tokenizer), + (['<|0.00|>', 'So,', 'uh', ',', '<|7.00|>'], + [['<|0.00|>'], + [' ', ' ', 'So', ','], + [' ', ' ', ' uh'], + [' ', ' ', ',', ' '], + ['<|7.00|>']], + [[50364], [220, 220, 6455, 11], [220, 220, 2232], [220, 220, 11, 220], [50714]] + ) + ) + + # Careful with the double spaces at the end... + tokens = [50364, 220, 220, 6455, 11, 220, 220, 2232, 220, 220, 11, 220, 220, 50714] + self.assertEqual( + split_tokens_on_spaces(tokens, tokenizer), + (['<|0.00|>', 'So,', 'uh', ',', '', '<|7.00|>'], + [['<|0.00|>'], + [' ', ' ', 'So', ','], + [' ', ' ', ' uh'], + [' ', ' ', ','], + [' ', ' '], + ['<|7.00|>']], + [[50364], [220, 220, 6455, 11], [220, 220, 2232], [220, 220, 11], [220, 220], [50714]] + ) + ) + + # Tokens that could be removed + tokens = [50364, 6024, 95, 8848, 7649, 8717, 38251, 11703, 3224, 51864] + self.assertEqual( + split_tokens_on_spaces(tokens, tokenizer), + (['<|0.00|>', 'الآذان', 'نسمّه', '<|30.00|>'], + [['<|0.00|>'], ['', ' الآ', 'ذ', 'ان'], [' ن', 'سم', 'ّ', 'ه'], ['<|30.00|>']], + [[50364], [6024, 95, 8848, 7649], [8717, 38251, 11703, 3224], [51864]] + ) + ) + + # issue #61 + # Special tokens that are not timestamps + tokens = [50414, 805, 12, 17, 50299, 11, 568, 12, 18, 12, 21, 11, 502, 12, 17, 12, 51464] + # 50299 is "<|te|>" and appears as "" + te = "" + self.assertEqual( + split_tokens_on_spaces(tokens, tokenizer), + (['<|1.00|>', f'3-2{te},', '2-3-6,', '1-2-', '<|22.00|>'], + [['<|1.00|>'], [' 3', '-', '2', f'{te}', ','], [' 2', '-', '3', '-','6', ','], [' 1', '-', '2', '-'], ['<|22.00|>']], + [[50414], [805, 12, 17, 50299, 11], [568, 12, 18, 12, 21, 11], [502, 12, 17, 12], [51464]]) + ) + + tokenizer = whisper.tokenizer.get_tokenizer(False, language="en") + + # Just a punctuation character + tokens = [50363, 764, 51813] + + _dot = "." if whisperversion < "20230314" else " ." + self.assertEqual( + split_tokens_on_spaces(tokens, tokenizer), + (['<|0.00|>', ".", '<|29.00|>'], + [['<|0.00|>'], [_dot], ['<|29.00|>']], + [[50363], [764], [51813]] + ) + ) diff --git a/whisper_timestamped/__init__.py b/whisper_timestamped/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..24fd61eeea212883b618d1fb974d40ab24f07ec0 --- /dev/null +++ b/whisper_timestamped/__init__.py @@ -0,0 +1,10 @@ +from whisper import available_models, _download, _MODELS # defined in __init__.py +from whisper import audio, decoding, model, normalizers, tokenizer, utils +from whisper.audio import load_audio, log_mel_spectrogram, pad_or_trim +from whisper.decoding import DecodingOptions, DecodingResult, decode, detect_language +from whisper.model import Whisper, ModelDimensions + +from .transcribe import transcribe_timestamped +from .transcribe import transcribe_timestamped as transcribe +from .transcribe import load_model +from .transcribe import __version__ \ No newline at end of file diff --git a/whisper_timestamped/make_subtitles.py b/whisper_timestamped/make_subtitles.py new file mode 100644 index 0000000000000000000000000000000000000000..bfc49ceda111efd3ac8065b082276aed26e79977 --- /dev/null +++ b/whisper_timestamped/make_subtitles.py @@ -0,0 +1,157 @@ +#!/usr/bin/env python3 + +import json +import string + +_punctuation = "".join(c for c in string.punctuation if c not in ["-", "'"]) + "。，！？：”、…" + +def split_long_segments(segments, max_length, use_space = True): + new_segments = [] + for segment in segments: + text = segment["text"] + if len(text) <= max_length: + new_segments.append(segment) + else: + meta_words = segment["words"] + # Note: we do this in case punctuation were removed from words + if use_space: + # Split text around spaces and punctuations (keeping punctuations) + words = text.split() + else: + words = [w["text"] for w in meta_words] + if len(words) != len(meta_words): + new_words = [w["text"] for w in meta_words] + print(f"WARNING: {' '.join(words)} != {' '.join(new_words)}") + words = new_words + current_text = "" + current_start = segment["start"] + current_best_idx = None + current_best_end = None + current_best_next_start = None + for i, (word, meta) in enumerate(zip(words, meta_words)): + current_text_before = current_text + if current_text and use_space: + current_text += " " + current_text += word + + if len(current_text) > max_length and len(current_text_before): + start = current_start + if current_best_idx is not None: + text = current_text[:current_best_idx] + end = current_best_end + current_text = current_text[current_best_idx+1:] + current_start = current_best_next_start + else: + text = current_text_before + end = meta_words[i-1]["end"] + current_text = word + current_start = meta["start"] + + current_best_idx = None + current_best_end = None + current_best_next_start = None + + new_segments.append({"text": text, "start": start, "end": end}) + + # Try to cut after punctuation + if current_text and current_text[-1] in _punctuation: + current_best_idx = len(current_text) + current_best_end = meta["end"] + current_best_next_start = meta_words[i+1]["start"] if i+1 < len(meta_words) else None + + if len(current_text): + new_segments.append({"text": current_text, "start": current_start, "end": segment["end"]}) + + return new_segments + +def format_timestamp(seconds: float, always_include_hours: bool = False, decimal_marker: str = '.'): + assert seconds >= 0, "non-negative timestamp expected" + milliseconds = round(seconds * 1000.0) + + hours = milliseconds // 3_600_000 + milliseconds -= hours * 3_600_000 + + minutes = milliseconds // 60_000 + milliseconds -= minutes * 60_000 + + seconds = milliseconds // 1_000 + milliseconds -= seconds * 1_000 + + hours_marker = f"{hours:02d}:" if always_include_hours or hours > 0 else "" + return f"{hours_marker}{minutes:02d}:{seconds:02d}{decimal_marker}{milliseconds:03d}" + +def write_vtt(result, file): + print("WEBVTT\n", file=file) + for segment in result: + print( + f"{format_timestamp(segment['start'])} --> {format_timestamp(segment['end'])}\n" + f"{segment['text'].strip().replace('-->', '->')}\n", + file=file, + flush=True, + ) + +def write_srt(result, file): + for i, segment in enumerate(result, start=1): + # write srt lines + print( + f"{i}\n" + f"{format_timestamp(segment['start'], always_include_hours=True, decimal_marker=',')} --> " + f"{format_timestamp(segment['end'], always_include_hours=True, decimal_marker=',')}\n" + f"{segment['text'].strip().replace('-->', '->')}\n", + file=file, + flush=True, + ) + +def cli(): + + import os + import argparse + + supported_formats = ["srt", "vtt"] + + parser = argparse.ArgumentParser( + description='Convert .word.json transcription files (output of whisper_timestamped) to srt or vtt, being able to cut long segments', + formatter_class=argparse.ArgumentDefaultsHelpFormatter + ) + parser.add_argument('input', type=str, help='Input json file, or input folder') + parser.add_argument('output', type=str, help='Output srt or vtt file, or output folder') + parser.add_argument('--max_length', default=200, help='Maximum length of a segment in characters', type=int) + parser.add_argument('--format', type=str, default="all", help='Output format (if the output is a folder, i.e. not a file with an explicit extension)', choices= supported_formats + ["all"]) + args = parser.parse_args() + + if os.path.isdir(args.input) or not max([args.output.endswith(e) for e in supported_formats]): + input_files = [f for f in os.listdir(args.input) if f.endswith(".words.json")] if os.path.isdir(args.input) else [os.path.basename(args.input)] + extensions = [args.format] if args.format != "all" else ["srt", "vtt"] + output_files = [[os.path.join(args.output, f[:-11] + "." + e) for e in extensions] for f in input_files] + if os.path.isdir(args.input): + input_files = [os.path.join(args.input, f) for f in input_files] + else: + input_files = [args.input] + if not os.path.isdir(args.output): + os.makedirs(args.output) + else: + input_files = [args.input] + output_files = [[args.output]] + if not os.path.isdir(os.path.dirname(args.output)): + os.makedirs(os.path.dirname(args.output)) + + for fn, outputs in zip(input_files, output_files): + with open(fn, "r", encoding="utf-8") as f: + transcript = json.load(f) + segments = transcript["segments"] + if args.max_length: + language = transcript["language"] + use_space = language not in ["zh", "ja", "th", "lo", "my"] + segments = split_long_segments(segments, args.max_length, use_space=use_space) + for output in outputs: + if output.endswith(".srt"): + with open(output, "w", encoding="utf-8") as f: + write_srt(segments, file=f) + elif output.endswith(".vtt"): + with open(output, "w", encoding="utf-8") as f: + write_vtt(segments, file=f) + else: + raise RuntimeError(f"Unknown output format for {output}") + +if __name__ == "__main__": + cli() \ No newline at end of file diff --git a/whisper_timestamped/transcribe.py b/whisper_timestamped/transcribe.py new file mode 100644 index 0000000000000000000000000000000000000000..9a444c29c703e3fec9d91ea6b1ae21ecaa2a54d8 --- /dev/null +++ b/whisper_timestamped/transcribe.py @@ -0,0 +1,3169 @@ +#!/usr/bin/env python3 + +__author__ = "Jérôme Louradour" +__credits__ = ["Jérôme Louradour"] +__license__ = "GPLv3" +__version__ = "1.15.4" + +# Set some environment variables +import os +os.environ['TF_CPP_MIN_LOG_LEVEL'] = '1' # Remove warning "This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)..." +os.environ['CUDA_DEVICE_ORDER'] = 'PCI_BUS_ID' # GPU in the right order + +# openai-whisper and pytorch +import whisper +import torch +import torch.nn.functional as F + +from importlib.util import find_spec +if find_spec("intel_extension_for_pytorch") is not None: + try: + import intel_extension_for_pytorch + except ImportError: + pass + +# For alignment +import numpy as np +import dtw +# from scipy.signal import medfilt as median_filter +from scipy.ndimage import median_filter # faster owing to https://github.com/openai/whisper/commit/f0083e7eb20d032390e42f6f6039947fa8669c93 +from scipy.signal import find_peaks + +# Additional +import string +import csv +import sys +import gzip, base64 +import copy +import re +import shutil +import json + +# Constant variables +from whisper.utils import format_timestamp +from whisper.audio import N_FRAMES, HOP_LENGTH, SAMPLE_RATE # 3000, 160, 16000 +AUDIO_SAMPLES_PER_TOKEN = HOP_LENGTH * 2 # 320 +AUDIO_TIME_PER_TOKEN = AUDIO_SAMPLES_PER_TOKEN / SAMPLE_RATE # 0.02 (sec) +SEGMENT_DURATION = N_FRAMES * HOP_LENGTH / SAMPLE_RATE # 30.0 (sec) + +# Logs +import logging +logger = logging.getLogger("whisper_timestamped") + +DEFAULT_BACKEND = "openai-whisper" # "transformers" +USE_EFFICIENT_BY_DEFAULT = True +TRUST_WHISPER_TIMESTAMP_BY_DEFAULT = True +DISFLUENCY_MARK = "[*]" + +try: + whisper_version = whisper.__version__ +except NameError: + whisper_version = "" +WHIPSER_GE_20230306 = whisper_version >= "20230306" +WHIPSER_GE_20230308 = whisper_version >= "20230308" + +def transcribe_timestamped( + # Main Whisper options + model, + audio, + language=None, + task="transcribe", + + # Additional options for word alignment + remove_punctuation_from_words=False, + compute_word_confidence=True, + include_punctuation_in_confidence=False, + refine_whisper_precision=0.5, + min_word_duration=0.02, # Was 0.04 before 1.11 + plot_word_alignment=False, + word_alignment_most_top_layers=None, # Was 6 before 1.9 + remove_empty_words=False, + use_backend_timestamps=False, + + # Reproducibility + seed=1234, + + vad=False, + detect_disfluencies=False, + trust_whisper_timestamps=TRUST_WHISPER_TIMESTAMP_BY_DEFAULT, + naive_approach=False, + + # Other Whisper options + temperature=0.0 if USE_EFFICIENT_BY_DEFAULT else (0.0, 0.2, 0.4, 0.6, 0.8, 1.0), + best_of=None, + beam_size=None, + patience=None, + length_penalty=None, + compression_ratio_threshold=2.4, + logprob_threshold=-1.0, + no_speech_threshold=0.6, + fp16=None, + condition_on_previous_text=True, + initial_prompt=None, + suppress_tokens="-1", + sample_len=None, + verbose=False, +): + """ + Transcribe an audio file using Whisper + + Parameters + ---------- + model: Whisper + The Whisper model instance. + + audio: Union[str, np.ndarray, torch.Tensor] + The path to the audio file to open, or the audio waveform in 16kHz. + + language: str + The language to use for the transcription. If None, the language is detected automatically. + + task: str + The task to perform: either "transcribe" or "translate". + + remove_punctuation_from_words: bool + If False, words will be glued with the next punctuation mark (if any). + If True, there will be no punctuation mark in the `words[:]["text"]` list. + It only affects these strings; This has no influence on the computation of the word confidence, whatever the value of `include_punctuation_in_confidence` is. + + include_punctuation_in_confidence: bool + Whether to include proba of punctuation in the computation of the (previous) word confidence. + + compute_word_confidence: bool + Whether to compute word confidence. + If True, a finer confidence for each segment will be computed as well. + + vad: bool or str in ["silero", "silero:3.1", "auditok"] or list of start/end timestamps pairs corresponding to speech (ex: [(0.0, 3.50), (32.43, 36.43)]) + Whether to perform voice activity detection (VAD) on the audio file, to remove silent parts before transcribing with Whisper model. + This should decrease hallucinations from the Whisper model. + When set to True, the default VAD algorithm is used (silero). + When set to a string, the corresponding VAD algorithm is used (silero, silero:3.1 or auditok). + Note that the library for the corresponding VAD algorithm must be installed. + + detect_disfluencies: bool + Whether to detect disfluencies (i.e. hesitations, filler words, repetitions, corrections, etc.) that Whisper model might have omitted in the transcription. + This should make the word timestamp prediction more accurate. + And probable disfluencies will be marked as special words "[*]". + + trust_whisper_timestamps: bool + Whether to rely on Whisper's timestamps to get approximative first estimate of segment positions (up to refine_whisper_precision). + + refine_whisper_precision: float + How much can we refine Whisper segment positions, in seconds. Must be a multiple of 0.02. + + min_word_duration: float + Minimum duration of a word, in seconds. If a word is shorter than this, timestamps will be adjusted. + + plot_word_alignment: bool + Whether to plot the word alignment for each segment. matplotlib must be installed to use this option. + + remove_empty_words: bool + Whether to remove words with no duration occuring at the end of segments (probable Whisper hallucinations). + + use_backend_timestamps: bool + Whether to use word timestamps provided by the backend (openai-whisper or transformers), instead of the ones computed by more complex heuristics of whisper-timestamped. + + seed: int + Random seed to use for temperature sampling, for the sake of reproducibility. + Choose None for unpredictable randomness. + + naive_approach: bool + Force the naive approach that consists in decoding twice the audio file, once to get the transcritpion and once with the decoded tokens to get the alignment. + Note that this approach is used anyway when beam_size is not None and/or when the temperature is a list with more than one element. + + temperature: float + Temperature for sampling. + + compression_ratio_threshold: float + If the gzip compression ratio is above this value, treat as failed. + + logprob_threshold: float + If the average log probability over sampled tokens is below this value, treat as failed. + + no_speech_threshold: float + If the no_speech probability is higher than this value AND the average log probability + over sampled tokens is below `logprob_threshold`, consider the segment as silent. + + condition_on_previous_text: bool + if True, the previous output of the model is provided as a prompt for the next window; + disabling may make the text inconsistent across windows, but the model becomes less prone to + getting stuck in a failure loop, such as repetition looping or timestamps going out of sync. + + initial_prompt: str + Optional text to provide as a prompt for the first window. + + suppress_tokens: str + Comma-separated list of token ids to suppress during sampling; + '-1' will suppress most special characters except common punctuations. + + verbose: bool + Whether to display the text being decoded to the console. If True, displays all the details, + If False, displays minimal details. If None, does not display anything + + Returns + ------- + A dictionary containing the resulting text ("text") and segment-level details ("segments"), and + the spoken language ("language"), which is detected when `decode_options["language"]` is None. + """ + + if seed is not None: + torch.manual_seed(seed) + torch.cuda.manual_seed_all(seed) + + # Check input options + assert refine_whisper_precision >= 0 and refine_whisper_precision / AUDIO_TIME_PER_TOKEN == round(refine_whisper_precision / AUDIO_TIME_PER_TOKEN), f"refine_whisper_precision must be a positive multiple of {AUDIO_TIME_PER_TOKEN}" + refine_whisper_precision_nframes = round(refine_whisper_precision / AUDIO_TIME_PER_TOKEN) + assert min_word_duration >= 0, f"min_word_duration must be a positive number" + assert word_alignment_most_top_layers is None or word_alignment_most_top_layers > 0, f"word_alignment_most_top_layers must be a strictly positive number" + + if isinstance(temperature, (list, tuple)) and len(temperature) == 1: + temperature = temperature[0] + if isinstance(temperature, (list, tuple)): # temperature fallback + naive_approach = True + elif temperature > 0 and best_of is not None and best_of > 1: # random sampling + naive_approach = True + if beam_size is not None: # beam-search + naive_approach = True + + # TODO: check if efficient approach is possible with transformers backend + # (careful: decoding heuristics are completely different from the ones used in openai-whisper) + if is_transformer_model(model) or use_backend_timestamps: + naive_approach = True + + # Input options + vad = check_vad_method(vad) + if isinstance(model, str): + model = load_model(model) + if fp16 is None: + fp16 = model.device != torch.device("cpu") + + # Safety check + input_stride = N_FRAMES // model.dims.n_audio_ctx + time_precision = input_stride * HOP_LENGTH / SAMPLE_RATE + assert time_precision == AUDIO_TIME_PER_TOKEN + + alignment_heads = get_alignment_heads(model) if word_alignment_most_top_layers is None else None + if alignment_heads is None and word_alignment_most_top_layers is None: + word_alignment_most_top_layers = 6 + + alignment_options = dict( + remove_punctuation_from_words=remove_punctuation_from_words, + compute_word_confidence=compute_word_confidence, + include_punctuation_in_confidence=include_punctuation_in_confidence, + detect_disfluencies=detect_disfluencies, + refine_whisper_precision_nframes=refine_whisper_precision_nframes, + plot_word_alignment=plot_word_alignment, + word_alignment_most_top_layers=word_alignment_most_top_layers, + alignment_heads=alignment_heads, + ) + whisper_options = dict( + language=language, + task=task, + fp16=fp16, + temperature=temperature, + best_of=best_of, + beam_size=beam_size, + patience=patience, + length_penalty=length_penalty, + condition_on_previous_text=condition_on_previous_text, + initial_prompt=initial_prompt, + suppress_tokens=suppress_tokens, + sample_len=sample_len, + verbose=verbose if (not vad or verbose is not True) else False, + ) + other_options = dict( + no_speech_threshold=no_speech_threshold, + logprob_threshold=logprob_threshold, + compression_ratio_threshold=compression_ratio_threshold, + ) + + if vad is not None: + audio = get_audio_tensor(audio) + audio, vad_segments, convert_timestamps = remove_non_speech(audio, method=vad, sample_rate=SAMPLE_RATE, plot=plot_word_alignment, avoid_empty_speech=True) + else: + vad_segments = None + + global num_alignment_for_plot + num_alignment_for_plot = 0 + + if naive_approach: + (transcription, words) = _transcribe_timestamped_naive(model, audio, + min_word_duration=0.0, # Was 0.04 before 1.11 + trust_whisper_timestamps=trust_whisper_timestamps, + use_backend_timestamps=use_backend_timestamps, + **alignment_options, **whisper_options, **other_options) + else: + (transcription, words) = _transcribe_timestamped_efficient(model, audio, + trust_whisper_timestamps=trust_whisper_timestamps, + **alignment_options, **whisper_options, **other_options) + if remove_empty_words: + # Remove words with empty duration happening at the end of segments, to remove some hallucinations + transcription, words = remove_last_null_duration_words(transcription, words, recompute_text=True) + + # Refine word positions + ensure_increasing_positions(words, min_duration=min_word_duration if trust_whisper_timestamps else 0) + + # Combine words and segments + whisper_segments = transcription["segments"] + for word in words: + if verbose and not naive_approach and not vad: + print_timestamped(word) + word.pop("tokens", None) + word.pop("tokens_indices", None) + if "avg_logprob_reliable" in word: + word.pop("avg_logprob_reliable") + idx_segment = word.pop("idx_segment") + assert idx_segment < len(whisper_segments), f"Fatal error: Got unexpected segment index {idx_segment} >= {len(whisper_segments)}" + segment = whisper_segments[idx_segment] + if "words" in segment: + segment["words"].append(word) + else: + segment["words"] = [word] + if refine_whisper_precision: + segment["start"] = word["start"] + if refine_whisper_precision: + segment["end"] = word["end"] + + if vad: + # Recompute timestamps to match the original audio + for segment in whisper_segments: + for word in segment.get("words", []): + word["start"], word["end"] = convert_timestamps(word["start"], word["end"]) + if verbose: + print_timestamped(word) + if refine_whisper_precision and len(segment.get("words", [])): + segment["start"] = segment["words"][0]["start"] + segment["end"] = segment["words"][-1]["end"] + else: + segment["start"], segment["end"] = convert_timestamps(segment["start"], segment["end"]) + + if vad_segments is not None: + transcription["speech_activity"] = [{"start":s, "end":e} for (s,e) in vad_segments] + + return transcription + +def _transcribe_timestamped_efficient( + model, + audio, + remove_punctuation_from_words, + compute_word_confidence, + include_punctuation_in_confidence, + refine_whisper_precision_nframes, + alignment_heads, + plot_word_alignment, + word_alignment_most_top_layers, + detect_disfluencies, + trust_whisper_timestamps, + use_timestamps_for_alignment = True, + # Whisper specific options + **whisper_options, +): + + # Get options + sample_len = whisper_options["sample_len"] + temperature = whisper_options["temperature"] + no_speech_threshold = whisper_options["no_speech_threshold"] + logprob_threshold = whisper_options["logprob_threshold"] + verbose = whisper_options["verbose"] + # Note: "on-the-fly" verbose is not implementable in the current state (we don't know the absolute position of the current chunk). See issue #18 + verbose_bugged = False + whisper_options["verbose"] = None if whisper_options["verbose"] is True else whisper_options["verbose"] # We will print intermediate results ourselves + + logit_filters = get_logit_filters(model, whisper_options) + language = whisper_options["language"] + tokenizer = get_tokenizer(model, task=whisper_options["task"], language=language) + + max_sample_len = sample_len or model.dims.n_text_ctx // 2 + n_ctx = model.dims.n_text_ctx + + debug = logger.getEffectiveLevel() >= logging.DEBUG + + word_alignment_most_top_layers = float("inf") if word_alignment_most_top_layers is None else word_alignment_most_top_layers + + # The main outcome + timestamped_word_segments = [] # list of timestamped word segments that have been collected so far + # Main variables to be accumulated + segment_tokens = [[]] # list of lists of token indices that have been collected so far (one list per segment) + segment_attweights = [[] for _ in range(min(word_alignment_most_top_layers, len(model.decoder.blocks)))] + # attention weights on the last segments + segment_avglogprobs = [] # average log probability for each segment (actually of the corresponding chunk, as computed by whisper) + segment_logprobs = [] # token log probabilities for each segment + # Variables related to options that can skip some segments + sot_index = None # index of the SOT token in the current set of processed tokens + no_speech_prob = None # no speech probability for the current 30 sec chunk + chunk_logprobs = [] # log probabilities for the current 30 sec chunk + chunk_tokens = [] # tokens for the current 30 sec chunk (list of Torch tensors) + chunk_tokens_nosot = [] # tokens for the current 30 sec chunk, without the SOT tokens (list of indices) + last_chunk_token = None # last token of the current chunk, that may be needed for corner cases + last_token_fallback = None # last token to use as a fallback if the model gets stuck + has_started = False # whether we have started decoding + mfcc = None # MFCC features for the current 30 sec chunk + new_mfcc = None # + num_inference_steps = 0 # number of inference steps performed so far (for debugging only) + language_probs = None # language detection probabilities + + def is_sot(curr_tokens): + return curr_tokens is None or len(curr_tokens) > 1 or curr_tokens[0] == tokenizer.sot + + def has_reached_decoding_limit(): + n = len(chunk_tokens_nosot) + 1 + m = n + (len(chunk_tokens[0]) if len(chunk_tokens) > 0 else 0) + return n + 1 >= max_sample_len or m > n_ctx + + def reset(add_segment, keep_last_token=True): + """ Reset the list of tokens for the current speech segment, and corresponding cross-attention weights """ + nonlocal segment_tokens, segment_attweights + if add_segment: + if keep_last_token: + segment_tokens.append([segment_tokens[-1][-1]]) + segment_attweights = [w[-1:] for w in segment_attweights] + else: + segment_tokens.append([]) + segment_attweights = [[] for w in segment_attweights] + segment_tokens[-2].pop(0) + elif len(segment_tokens[-1]) > 0: + if debug: + logger.debug(f"Reset last segment: {tokenizer.decode_with_timestamps(segment_tokens[-1])}") + segment_tokens[-1] = [] + segment_attweights = [[] for w in segment_attweights] + + saw_consecutive_timestamps = False + def must_flush_segment(curr_tokens): + """ Return whether or not the previously collected tokens must be used to add a new speech segment """ + nonlocal segment_tokens, saw_consecutive_timestamps, chunk_tokens_nosot + + if not is_sot(curr_tokens): + is_timestamp = curr_tokens[0] >= tokenizer.timestamp_begin + is_previous_timestamp = segment_tokens[-1][-1] >= tokenizer.timestamp_begin if len(segment_tokens[-1]) > 0 else False + consecutive_timestamps = is_timestamp and is_previous_timestamp + if consecutive_timestamps: + saw_consecutive_timestamps = True + return consecutive_timestamps + else: # Several tokens as a prompt or must flush last segments + + must_flush = len(segment_tokens[-1]) > 1 and not saw_consecutive_timestamps + if not must_flush and WHIPSER_GE_20230306: # If the last token is a timestamp, the last segment is used + if last_chunk_token is None: + must_flush = (len(segment_tokens[-1]) > 2 and segment_tokens[-1][-1] >= tokenizer.timestamp_begin) + else: + must_flush = (last_chunk_token >= tokenizer.timestamp_begin) + if not must_flush and trust_whisper_timestamps: + # Discard the end of the last transcription + reset(False) + saw_consecutive_timestamps = False + return must_flush + + index_begin_30sec_chunck = 0 + def get_index_begin_30sec_chunck(curr_tokens): + nonlocal index_begin_30sec_chunck, has_started + + if is_sot(curr_tokens) and has_started: + if trust_whisper_timestamps: + res = index_begin_30sec_chunck + index_begin_30sec_chunck = len(segment_tokens)-1 + else: + res = len(segment_tokens)-1 + return res + + def align_last_segment(curr_tokens=None): + nonlocal segment_tokens, segment_attweights, timestamped_word_segments, has_started, no_speech_prob, chunk_tokens, chunk_tokens_nosot, chunk_logprobs, mfcc, new_mfcc, logit_filters, index_begin_30sec_chunck, last_token_fallback, num_inference_steps + + if debug and trust_whisper_timestamps: + logger.debug(f"Add segment {len(timestamped_word_segments)+1} at step {num_inference_steps}:\n\t{tokenizer.decode_with_timestamps(segment_tokens[-1])}") + + tokens = segment_tokens[-1][1:] + + # When the decoding hit the max limit (number of tokens) -- usually when the language model gets stuck -- + # then we have to recover the last token from what is send to the decoder + unfinished_decoding = has_reached_decoding_limit() + last_is_not_timestamp = len(tokens) and tokens[-1] < tokenizer.timestamp_begin + last_token_reliable = True + + if unfinished_decoding: + logger.debug(f"WARNING: decoding hit the max limit for segment {segment_tokens[-1]} (It usually happens when the language model gets stuck)") + # The last token chosen is in the prompt for the new chunk + if curr_tokens is not None and curr_tokens[0] == tokenizer.sot_prev: + index_sot = (curr_tokens == tokenizer.sot).nonzero(as_tuple=True) + assert len(index_sot) == 1 + index_sot = index_sot[0].item() + assert index_sot > 0 + last_token_fallback = curr_tokens[index_sot-1].item() + logger.debug(f" Guessed last token from the prompt for the new chunk: {last_token_fallback}") + # Fallback for the last segment, or without prompt: Assume greedy decoding + else: + last_token_fallback = torch.argmax(chunk_logprobs[-1]).item() if last_chunk_token is None else last_chunk_token + last_token_reliable = (temperature == 0) + logger.debug(f" Guess last token using probas (assuming greedy decoding): {last_token_fallback}") + if debug: + logger.debug(f"WARNING: also add last token: {tokenizer.decode_with_timestamps([last_token_fallback])}") + + tokens.append(last_token_fallback) + segment_tokens[-1].append(last_token_fallback) + attention_weights = [torch.cat(w, dim=-2) for w in segment_attweights] + last_logprobs = chunk_logprobs[-1] + elif last_is_not_timestamp: # was emitted early, without a timestamp before + logger.debug(f"WARNING: end timestamp not produced. Adding <|endoftext|>") + tokens.append(tokenizer.eot) + segment_tokens[-1].append(tokenizer.eot) + attention_weights = [torch.cat(w, dim=-2) for w in segment_attweights] + last_logprobs = chunk_logprobs[-1] + else: + attention_weights = [torch.cat(w[:-1], dim=-2) for w in segment_attweights] + last_logprobs = chunk_logprobs[-2] + + # Check prediction of last token + end_token = tokens[-1] + if end_token >= tokenizer.timestamp_begin: + start_token = tokens[0] + assert start_token >= tokenizer.timestamp_begin + # If Whisper prediction of the end is obviously wrong, we predict it again (constrained) + if end_token <= start_token: + new_end_token = last_logprobs[start_token+1:].argmax() + start_token + 1 + tokens[-1] = new_end_token.item() + if debug: + logger.debug(f"Re-estimated end token {tokenizer.decode_with_timestamps([new_end_token])} (was {tokenizer.decode_with_timestamps([end_token])}) to be after start token {tokenizer.decode_with_timestamps([start_token])}") + + if len(tokens) <= 1: + # Corner case: nothing in between timestamps + ws = [] + else: + ws = perform_word_alignment( + tokens, + attention_weights, + tokenizer, + use_space=should_use_space(language), + alignment_heads=alignment_heads, + remove_punctuation_from_words=remove_punctuation_from_words, + refine_whisper_precision_nframes=refine_whisper_precision_nframes, + detect_disfluencies=detect_disfluencies, + unfinished_decoding=unfinished_decoding, + mfcc=mfcc, + plot=plot_word_alignment, + debug=debug, + ) + + add_segment = len(ws) > 0 + if add_segment: + timestamped_word_segments.append(ws) + else: + logger.debug(f"Not added!") + reset(add_segment, not is_sot(curr_tokens)) + + return add_segment, unfinished_decoding, last_token_reliable + + def may_flush_segment(curr_tokens = None): + """ Add a speech segment with the new tokens if necessary. + May also remove the last collected segments if filtered out by Whisper (no_speech_prob <= no_speech_threshold) + """ + nonlocal segment_tokens, segment_attweights, timestamped_word_segments, segment_logprobs, has_started, no_speech_prob, chunk_tokens, chunk_tokens_nosot, chunk_logprobs, mfcc, new_mfcc, logit_filters, index_begin_30sec_chunck, last_token_fallback, num_inference_steps, last_chunk_token + + # Check if a new segment should be added + unfinished_decoding = False + last_token_reliable = True + + if must_flush_segment(curr_tokens) and trust_whisper_timestamps: + _, unfinished_decoding, last_token_reliable = align_last_segment(curr_tokens) + + i_start = get_index_begin_30sec_chunck(curr_tokens) + + # All segments from previous 30sec chunck have been collected + if i_start is not None: + + if not trust_whisper_timestamps: + + tokens = torch.Tensor(segment_tokens[-1]).int() + idx_task = torch.where(tokens==tokenizer.sot_sequence[-1])[0][0].item() # index of <|transcribe|> + + is_special = tokens.ge(tokenizer.eot) + # Remove prompt + is_special[:idx_task] = True + # Keep begin timestamp + is_special[idx_task:idx_task+2] = False + + is_timestamp = tokens.ge(tokenizer.timestamp_begin) + consecutive = torch.where(is_timestamp[1:] & is_timestamp[:-1])[0] + if (WHIPSER_GE_20230306 or has_reached_decoding_limit()) and ( + (is_timestamp[-1] and not is_timestamp[-2]) if last_chunk_token is None else + last_chunk_token >= tokenizer.timestamp_begin and not is_timestamp[-2] + ): + consecutive = torch.cat([consecutive, torch.Tensor([len(tokens)-1]).int()]) + last_is_timestamp = True + if len(consecutive): + # Remove last tokens + is_special[consecutive[-1]+1:] = True + # Keep end timestamp + is_special[consecutive[-1]] = False + elif is_timestamp[-1]: + # Keep end timestamp + is_special[-1] = False + else: + last_is_timestamp = False + + if use_timestamps_for_alignment and len(consecutive): + # Keep all timestamps + is_special[idx_task+2:consecutive[-1]] = False + + # Do remove what has to be removed + is_next_achar = ~torch.cat([is_special[1:], torch.Tensor([False]).bool()]) + for i, weights in enumerate(segment_attweights): + assert len(weights) == len(tokens), f"{len(weights)} attention weights != {len(tokens)}" + # We must remove attention weights used to predict timestamp tokens + segment_attweights[i] = [w for s, w in zip(is_next_achar, weights) if s] + tokens_filtered = tokens[~is_special] + assert len(segment_attweights[0]) == len(tokens_filtered), f"{len(segment_attweights[0])} attention weights != {len(tokens_filtered)} " + + # Replace first and last timestamp + orig_start, orig_end = tokens_filtered[1].item(), tokens_filtered[-1].item() + tokens_filtered[1] = tokenizer.timestamp_begin # <|0.00|> + if last_is_timestamp: + tokens_filtered[-1] = tokenizer.timestamp_begin + N_FRAMES // 2 # <|30.00|> + segment_tokens[-1] = tokens_filtered.tolist() + + # Do alignment + added, unfinished_decoding, last_token_reliable = align_last_segment() + + # Re-split into segments (if necessary) + if added: + if len(consecutive) > 1: + segments_timestamped_concat = timestamped_word_segments[-1] + new_segments_timestamped = [] + new_segment_tokens = [] + start = idx_task+1 + i_word = 0 + for i, end in enumerate(consecutive): + end = end.item() + new_segment_tokens.append(tokens[start:end+1].tolist()) + if debug: + logger.debug(f"Add segment {len(timestamped_word_segments)+i}:\n\t{tokenizer.decode_with_timestamps(new_segment_tokens[-1])}") + total_length = end - start - 1 + start = end+1 + length = 0 + new_segments_timestamped.append([]) + while length < total_length: + if not use_timestamps_for_alignment and i_word == len(segments_timestamped_concat): + # This can happen in the case of "..." + assert total_length == 1 and i == len(consecutive)-1, "Unexpected situation!" + break + assert i_word < len(segments_timestamped_concat), f"i_word={i_word} < len(segments_timestamped_concat)={len(segments_timestamped_concat)}" + word = segments_timestamped_concat[i_word] + new_segments_timestamped[-1].append(word) + length += len(word["tokens_indices"]) + i_word += 1 + # This can be non zero, when a punctuation (alone in a segment) is glued to the previous segment + if use_timestamps_for_alignment: + assert length == total_length, f"length={length} != total_length={total_length}" + elif length > total_length: + delta = length - total_length + word = new_segments_timestamped[-1][-1] + word_tokindices = word["tokens_indices"] + word_tokens = word["tokens"] + word["tokens_indices"] = word_tokindices[:-delta] + word["tokens"] = word_tokens[:-delta] + word["word"] = "".join(word_tokens[:-delta]) + i_word -= 1 + t = segments_timestamped_concat[i_word]["end"] + segments_timestamped_concat[i_word] = dict( + text="".join(word_tokens[-delta:]), + start=t, end=t, # Word without timestamp + tokens=word_tokens[-delta:], + tokens_indices=word_tokindices[-delta:], + ) + + assert i_word == len(segments_timestamped_concat) + + segment_tokens = segment_tokens[:-2] + new_segment_tokens + [segment_tokens[-1]] + timestamped_word_segments = timestamped_word_segments[:-1] + new_segments_timestamped + + else: + + # Recover start and end token + segment = segment_tokens[-2] + tokenizer.decode_with_timestamps([orig_start,orig_end]) + segment[0] = orig_start + if last_is_timestamp: + segment[-1] = orig_end + + if debug: + logger.debug(f"Add segment {len(timestamped_word_segments)}:\n\t{tokenizer.decode_with_timestamps(segment)}") + + if unfinished_decoding: + timestamped_word_segments[-1][-1]["avg_logprob_reliable"] = last_token_reliable + + reset(False) + + mfcc = new_mfcc + + n_segments = len(segment_tokens)-1 + + # Get word confidence and/or check if previous segments shoud have been skipped + should_skip = False + if compute_word_confidence or no_speech_threshold is not None: + + # no voice activity check + should_skip = (no_speech_prob > no_speech_threshold) if (no_speech_threshold is not None) else False + if compute_word_confidence or (should_skip and logprob_threshold is not None): + n = len(chunk_logprobs) + if n == len(chunk_tokens_nosot): + chunk_tokens_nosot = chunk_tokens_nosot[1:] + if unfinished_decoding: + assert last_token_fallback is not None + last_tokens = [last_token_fallback] + timestamped_word_segments[-1][-1]["avg_logprob_reliable"] = last_token_reliable + n += 1 + elif has_reached_decoding_limit(): + # there were segments in the 30sec chunck, and then the LM got stuck + last_tokens = [torch.argmax(chunk_logprobs[-1]).item()] + timestamped_word_segments[-1][-1]["avg_logprob_reliable"] = (temperature == 0) + else: + last_tokens = [tokenizer.eot] + chunck_indices = chunk_tokens_nosot + last_tokens + assert len(chunk_logprobs) == len(chunck_indices), f"{len(chunk_logprobs)} != {len(chunck_indices)}" + logprobs = torch.cat([logprob[i].unsqueeze(0) for (logprob, i) in zip(chunk_logprobs, chunck_indices)]) + assert min([p.isfinite().item() for p in logprobs]), \ + f"Got infinite logprob among ({len(logprobs)}) {[(i, tokenizer.decode_with_timestamps([i]), v.item()) for (i,v) in zip(chunck_indices, logprobs)]}" + sum_logprob = sum(logprobs) + avg_logprob = sum_logprob/n + # don't skip if the logprob is high enough, whatever the no_speech_prob is + if logprob_threshold is not None and avg_logprob > logprob_threshold: + should_skip = False + + if should_skip: + logger.debug(f"Skipping last {n_segments-i_start} segments (no_speech_prob {no_speech_prob} > {no_speech_threshold} and avg_logprob {avg_logprob} < {logprob_threshold})") + index_begin_30sec_chunck -= n_segments-i_start + segment_tokens = segment_tokens[:i_start] + [segment_tokens[-1]] + timestamped_word_segments = timestamped_word_segments[:i_start] + elif compute_word_confidence: + avg_logprob = avg_logprob.item() + i_token_end = -1 + for i in range(i_start, n_segments): + tokens = segment_tokens[i] + i_token_start = i_token_end + 1 + i_token_end = i_token_start + len(tokens) + assert chunck_indices[i_token_start:i_token_end] == tokens, f"Inconsistent token list {tokenizer.decode_with_timestamps(chunck_indices[i_token_start:i_token_end])} != {tokenizer.decode_with_timestamps(tokens)}" + i_token_start += 1 # skip sos (start time) + if not unfinished_decoding or i != n_segments-1: + i_token_end -= 1 # skip eos (end time) + segment_logprobs.append(logprobs[i_token_start:i_token_end]) + segment_avglogprobs.append(avg_logprob) + else: + for i in range(i_start, n_segments): + segment_logprobs.append(None) + segment_avglogprobs.append(None) + + else: + for i in range(i_start, n_segments): + segment_logprobs.append(None) + segment_avglogprobs.append(None) + + if verbose_bugged and not should_skip: + for segment in timestamped_word_segments[i_start:]: + for word in segment: + print_timestamped(word) + + # Reset counters + chunk_tokens = [] + chunk_tokens_nosot = [] + chunk_logprobs = [] + no_speech_prob = None + + def hook_attention_weights(layer, ins, outs, index): + nonlocal segment_attweights + # In old version of whisper, output is a single tensor + assert isinstance(outs, tuple) and len(outs) == 2, "whisper seems to be outdated, please update it (pip install --upgrade --no-deps --force-reinstall git+https://github.com/openai/whisper.git)" + if not has_started: + return + w = outs[-1] + # Only the last attention weights is useful + if w.shape[-2] > 1: + w = w[:, :, -1:, :] + segment_attweights[index].append(w.cpu()) + + def hook_mfcc(layer, ins, outs): + nonlocal new_mfcc, mfcc + new_mfcc = ins[0] + if mfcc is None: + mfcc = new_mfcc + + def hook_input_tokens(layer, ins, outs): + nonlocal segment_tokens, sot_index, chunk_tokens, chunk_tokens_nosot, logit_filters, has_started, language, num_inference_steps + num_inference_steps += 1 + + curr_tokens = ins[0] + assert curr_tokens.shape[0] == 1, "Batch decoding is not supported" + curr_tokens = curr_tokens.squeeze(0) + + if is_sot(curr_tokens): + chunk_prompt = curr_tokens.tolist() + if language is None: + if len(curr_tokens) > 1: + language = tokenizer.decode(curr_tokens[-2:-1]) + language = language[2:-2] # remove trailing "<|" and "|>" + whisper_options["language"] = language + + if verbose and not whisper_options["verbose"] and len(curr_tokens) > 1: + # Reproduce whisper verbose (2/2) + print(f"Detected language: {whisper.tokenizer.LANGUAGES[language].title()}") + sys.stdout.flush() + + logit_filters = get_logit_filters(model, whisper_options, prompt = chunk_prompt[1:-len(tokenizer.sot_sequence)]) + + may_flush_segment(curr_tokens) + + # Get the index of the <|startoftranscript|> tokens (to get proba of silence later) + if is_sot(curr_tokens): + has_started = len(curr_tokens) > 1 or not model.is_multilingual + if no_speech_threshold is not None: + sot_index = curr_tokens.tolist().index(tokenizer.sot) + else: + sot_index = None + + # Keep the last token only + if has_started: + segment_tokens[-1].append(curr_tokens[-1].item()) + + # Accumulate tokens + if has_started: + chunk_tokens.append(curr_tokens) + if not is_sot(curr_tokens): + chunk_tokens_nosot.append(curr_tokens[-1].item()) + else: + if verbose and not whisper_options["verbose"]: + # Reproduce whisper verbose (1/2) + print("Detecting language using up to the first 30 seconds. Use `--language` to specify the language") + + embedding_weights = None + def hook_output_logits(layer, ins, outs): + nonlocal no_speech_prob, chunk_logprobs, segment_tokens, chunk_tokens, chunk_tokens_nosot, last_chunk_token, embedding_weights, has_started, language, language_probs + + if embedding_weights is None: + embedding_weights = torch.transpose(model.decoder.token_embedding.weight, 0, 1).to(outs[0].dtype) + + # Get the probability of silence + if sot_index is not None and no_speech_prob is None: + logits = (outs[0][sot_index,:] @ embedding_weights).float() + logits = logits.softmax(dim=-1) + no_speech_prob = logits[tokenizer.no_speech].item() + + # Get language probabilities + if language is None and sot_index is not None and model.is_multilingual: + index_start = tokenizer.sot + 1 + index_end = index_start + len(tokenizer.all_language_tokens) + logits = (outs[0][sot_index,:] @ embedding_weights).float() + language_probs = logits[index_start:index_end].softmax(dim=-1) + language_probs = dict(zip(whisper.tokenizer.LANGUAGES, language_probs.tolist())) + + # Get the log-probabilities of tokens (we don't know yet which one will be chosen) + if has_started: + logits = (outs[0][-1:,:] @ embedding_weights).float() + tokens = torch.cat(chunk_tokens).unsqueeze(0) + for logit_filter in logit_filters: + logit_filter.apply(logits, tokens) + logits = F.log_softmax(logits.squeeze(0), dim=-1) + chunk_logprobs.append(logits) + + if WHIPSER_GE_20230306 and has_reached_decoding_limit(): + last_chunk_token = torch.argmax(logits).item() + else: + last_chunk_token = None + + try: + + # Add hooks to the model, to get tokens and attention weights on the fly + all_hooks = [] + all_hooks.append(model.encoder.conv1.register_forward_hook(hook_mfcc)) + all_hooks.append(model.decoder.token_embedding.register_forward_hook(hook_input_tokens)) + nblocks = len(model.decoder.blocks) + j = 0 + for i, block in enumerate(model.decoder.blocks): + if i < nblocks - word_alignment_most_top_layers: + continue + all_hooks.append( + block.cross_attn.register_forward_hook( + lambda layer, ins, outs, index=j: hook_attention_weights(layer, ins, outs, index)) + ) + j += 1 + if compute_word_confidence or no_speech_threshold is not None: + all_hooks.append(model.decoder.ln.register_forward_hook(hook_output_logits)) + + transcription = model.transcribe(audio, **whisper_options) + + finally: + + # Remove hooks + for hook in all_hooks: + hook.remove() + + # Finalize (collect last segment) + may_flush_segment() + segment_tokens.pop(-1) + + token_special_idx = min(tokenizer.sot, tokenizer.eot) + def filter_tokens(tokens): + while len(tokens) and tokens[0] >= token_special_idx: + tokens = tokens[1:] + while len(tokens) and tokens[-1] >= token_special_idx: + tokens = tokens[:-1] + return tokens + + assert len(segment_tokens) == len(timestamped_word_segments), f"Inconsistent number of segments: tokens ({len(segment_tokens)}) != timestamped_word_segments ({len(timestamped_word_segments)})" + assert len(segment_avglogprobs) == len(segment_tokens), f"Inconsistent number of segments: avg logprobs ({len(segment_avglogprobs)}) != tokens ({len(segment_tokens)})" + assert len(segment_logprobs) == len(segment_tokens), f"Inconsistent number of segments: logprobs ({len(segment_logprobs)}) != tokens ({len(segment_tokens)})" + + whisper_segments = transcription["segments"] + # See issue 64: some segments may have empty text + if any(not s["text"] for s in whisper_segments): + whisper_segments = [s for s in whisper_segments if s["text"]] + l1 = len(whisper_segments) + l2 = len(timestamped_word_segments) + if l1 != l2 and l1 != 0: + logger.warning(f"Inconsistent number of segments: whisper_segments ({l1}) != timestamped_word_segments ({l2})") + assert l1 == l2 or l1 == 0, f"Inconsistent number of segments: whisper_segments ({l1}) != timestamped_word_segments ({l2})" + + logger.debug("Compile results") + words = [] + for i, (segment, timestamped_words, token, avglogprob, logprobs) in enumerate(zip(whisper_segments, timestamped_word_segments, segment_tokens, segment_avglogprobs, segment_logprobs)): + timestamped_tokens = filter_tokens(token) + whisper_tokens = filter_tokens(segment["tokens"]) + if timestamped_tokens != whisper_tokens: + if len(timestamped_tokens) == len(whisper_tokens) + 1: + logger.warning(f"An additional token was added on segment {i}") + elif WHIPSER_GE_20230306 and len(whisper_tokens) == 0: + logger.warning(f"Whisper has empty segment {i}") + assert segment["end"] == segment["start"], f"Fatal Error: Got empty segment {i} with non-zero duration" + segment["tokens"] = timestamped_tokens + segment["text"] = tokenizer.decode(timestamped_tokens) + else: + assert len(timestamped_tokens) < len(whisper_tokens) and timestamped_tokens == whisper_tokens[:len(timestamped_tokens)], \ + f"Fatal Error: Got inconsistent text for segment {i}:\n({len(timestamped_tokens)})\n{tokenizer.decode_with_timestamps(timestamped_tokens)}\n{timestamped_tokens}\n!=\n({len(whisper_tokens)})\n{tokenizer.decode_with_timestamps(whisper_tokens)}\n{whisper_tokens[:len(timestamped_tokens)]}" + segment["tokens"] = token if WHIPSER_GE_20230306 else timestamped_tokens # tokens include special timestamp tokens since 20230306 + segment["text"] = tokenizer.decode(segment["tokens"]) + logger.warning(f"Text had to be shortned on segment {i}:\n{tokenizer.decode(timestamped_tokens)}\n!=\n{tokenizer.decode(whisper_tokens)}") + timestamped_words[-1]["avg_logprob_reliable"] = False + + offset = segment["seek"] * HOP_LENGTH / SAMPLE_RATE + for timestamped_word in timestamped_words: + timestamped_word["start"] += offset + timestamped_word["end"] += offset + timestamped_word["idx_segment"] = i + + if compute_word_confidence: + if "avg_logprob_reliable" not in timestamped_words[-1] or timestamped_words[-1]["avg_logprob_reliable"]: + # assert abs(segment["avg_logprob"] - avglogprob) < 1e-2, f"Fatal Error: Got inconsistent logprob for segment {i}: {segment['avg_logprob']} != {avglogprob}" + if abs(segment["avg_logprob"] - avglogprob) >= 1e-2: + logger.warning(f"Recomputed different logprob for segment {i}: {avglogprob} != {segment['avg_logprob']}") + if include_punctuation_in_confidence: + segment["confidence"] = round_confidence(logprobs.mean().exp().item()) + else: + logprobs_nopunc = [] + i_end = 0 + for timestamped_word in timestamped_words: + i_start = i_end + tokens = timestamped_word["tokens"] + i_end += len(tokens) + + assert i_end <= len(logprobs), f"Fatal Error: Got out-of-bound index for segment {i}: {i_end} > {len(logprobs)}" + if include_punctuation_in_confidence: + word_logprobs = logprobs[i_start:i_end] + else: + while len(tokens) > 1 and len(tokens[-1]) and tokens[-1][-1] in _punctuation: # Note: look at the last character of token, to take into account "...", "!!", etc. + tokens = tokens[:-1] + word_logprobs = logprobs[i_start:i_start + len(tokens)] + logprobs_nopunc.append(word_logprobs) + + timestamped_word["confidence"] = round_confidence(word_logprobs.mean().exp().item() if len(word_logprobs) else 0.0) + + if i_end not in [len(logprobs), len(logprobs)-1]: + logger.warning(f"Got inconsistent length for segment {i} ({len(logprobs)} != {i_end}). Some words have been ignored.") + if not include_punctuation_in_confidence: + logprobs_nopunc = torch.cat(logprobs_nopunc) + segment["confidence"] = round_confidence(logprobs_nopunc.mean().exp().item()) + + words.extend(timestamped_words) + + if language_probs: + transcription["language_probs"] = language_probs + + return transcription, words + +def _transcribe_timestamped_naive( + model, + audio, + remove_punctuation_from_words, + compute_word_confidence, + include_punctuation_in_confidence, + refine_whisper_precision_nframes, + use_backend_timestamps, + alignment_heads, + plot_word_alignment, + word_alignment_most_top_layers, + detect_disfluencies, + trust_whisper_timestamps, + min_word_duration, + **whisper_options, +): + verbose = whisper_options["verbose"] + whisper_options["verbose"] = None if whisper_options["verbose"] is True else whisper_options["verbose"] # We will print intermediate results ourselves + language = whisper_options["language"] + refine_whisper_precision_sec = refine_whisper_precision_nframes * AUDIO_TIME_PER_TOKEN + + word_alignment_most_top_layers = float("inf") if word_alignment_most_top_layers is None else word_alignment_most_top_layers + + audio = get_audio_tensor(audio) + audio_duration = audio.shape[-1] / SAMPLE_RATE + + if verbose and language is None and not whisper_options["verbose"]: + # Reproduce whisper verbose (1/2) + print("Detecting language using up to the first 30 seconds. Use `--language` to specify the language") + + tokenizer = get_tokenizer(model, task=whisper_options["task"], language=language) + + transformer_backend = is_transformer_model(model) + if transformer_backend: + # Additional options specific to transformer models + whisper_options["remove_punctuation_from_words"] = remove_punctuation_from_words + whisper_options["use_token_timestamps"] = use_backend_timestamps + else: + whisper_options["word_timestamps"] = use_backend_timestamps + + language_probs = None + def hook_output_logits(layer, ins, outs): + nonlocal language_probs, tokenizer + + # Get language probabilities + if language is None and language_probs is None: + if outs.shape[1] == 1: + embedding_weights = torch.transpose(model.decoder.token_embedding.weight, 0, 1).to(outs[0].dtype) + index_start = tokenizer.sot + 1 + index_end = index_start + len(tokenizer.all_language_tokens) + logits = (outs[0][0,:] @ embedding_weights).float() + language_probs = logits[index_start:index_end].softmax(dim=-1) + language_probs = dict(zip(whisper.tokenizer.LANGUAGES, language_probs.tolist())) + else: + language_probs = False + + all_hooks = [] + if model.is_multilingual: + all_hooks.append(model.decoder.ln.register_forward_hook(hook_output_logits)) + + try: + model.alignment_heads = alignment_heads # Avoid exception "AttributeError: 'WhisperUntied' object has no attribute 'alignment_heads'. Did you mean: 'set_alignment_heads'?"" + transcription = model.transcribe(audio, **whisper_options) + finally: + for hook in all_hooks: + hook.remove() + + if not transformer_backend and verbose and language is None and not whisper_options["verbose"]: + # Reproduce whisper verbose (2/2) + print(f"Detected language: {whisper.tokenizer.LANGUAGES[transcription['language']].title()}") + sys.stdout.flush() + + # End early if timestamps have been computed by the backend + if transcription.get("segments") and "words" in transcription["segments"][0]: + words = [] + for i_segment, segment in enumerate(transcription["segments"]): + ws = segment.pop("words", []) + for w in ws: + # Rename openai-whisper -> whisper-timestamped + if "word" in w: w["text"] = w.pop("word") + if "probability" in w: w["confidence"] = round_confidence(w.pop("probability")) + w["idx_segment"] = i_segment + words.extend(ws) + if language_probs: + transcription["language_probs"] = language_probs + return transcription, words + + language = norm_language(transcription.get("language", language)) + use_space = should_use_space(language) + + n_mels = model.dims.n_mels if hasattr(model.dims, "n_mels") else 80 + + attention_weights = [[] for _ in range(min(word_alignment_most_top_layers, len(model.decoder.blocks)))] + + try: + + all_hooks = [] + + # Hook the model + nblocks = len(model.decoder.blocks) + j = 0 + for i, block in enumerate(model.decoder.blocks): + if i < nblocks - word_alignment_most_top_layers: + continue + def hook(layer, ins, outs, index=j): + if is_transformer_model(model): + attention_weights[index] = outs[1].log() + else: + attention_weights[index] = outs[1] + all_hooks.append( + block.cross_attn.register_forward_hook( + hook + # lambda layer, ins, outs, index=j: attention_weights.__setitem__(index, outs[1]) + ) + ) + j += 1 + + + # When not relying on Whisper timestamps + current_tokens = [] + token_to_idx_segment = [] + + words = [] + previous_end = 0 + whisper_segments = transcription["segments"] + for i_segment, segment in enumerate(whisper_segments): + + # Note: this could also be a fix to issue #61 where a "<|te|>" token was predicted + # segment["tokens"] = [t for t in segment["tokens"] if t < tokenizer.eot or t >= tokenizer.timestamp_begin] + + start = end = tokens = None + if trust_whisper_timestamps: + + start = segment["start"] + end = segment["end"] + if end < start: + # Whisper is wrong on the prediction of segment end + end = min(audio_duration, start + SEGMENT_DURATION) + + start_margin_min = start - refine_whisper_precision_sec + start_margin_max = start + refine_whisper_precision_sec + if start >= audio_duration - min_word_duration or (previous_end >= start_margin_min and previous_end <= start_margin_max): + # Make start as accurate as possible (as the decoding will start with timestamp <|0|>) + start = previous_end + else: + # Fallback + start = start_margin_min + + if start > audio_duration - min_word_duration: + # Skip last segment if too short + logger.warning(f"Skipping segment outside of audio duration {audio_duration} (original: {segment['start']}-{segment['end']}, new: {start}-XXX)") + continue + + end_margin_min = end - refine_whisper_precision_sec + end_margin_max = end + refine_whisper_precision_sec + if i_segment < len(whisper_segments) - 1: + # Try to enforce: + # end + min_word_duration <= next start + refine_whisper_precision_sec + end_margin_max2 = whisper_segments[i_segment + 1]["start"] + refine_whisper_precision_sec - min_word_duration + if end_margin_max2 >= end_margin_min: + end_margin_max = min(end_margin_max2, end_margin_max) + end = min(audio_duration, end_margin_max) + + if end < start + min_word_duration: + logger.warning(f"Got super short segment (original from whisper: {segment['start']}-{segment['end']}, new: {start, end})") + end = min(audio_duration, start + min_word_duration) + if end <= start: + logger.warning(f"Skipping this short segment occuring too close to the end of the audio") + continue + + tokens = segment["tokens"] + + else: + + seek = segment["seek"] + new_tokens = segment["tokens"] + if not len(new_tokens): + continue + # Add timestamps that will be needed after + if new_tokens[0] < tokenizer.timestamp_begin: + relative_start = segment["start"] - (seek * HOP_LENGTH / SAMPLE_RATE) + start_token = round(relative_start * SAMPLE_RATE / AUDIO_SAMPLES_PER_TOKEN) + tokenizer.timestamp_begin + new_tokens = [start_token] + new_tokens + if new_tokens[-1] < tokenizer.timestamp_begin: + relative_end = segment["end"] - (seek * HOP_LENGTH / SAMPLE_RATE) + end_token = round(relative_end * SAMPLE_RATE / AUDIO_SAMPLES_PER_TOKEN) + tokenizer.timestamp_begin + new_tokens = new_tokens + [end_token] + + current_tokens.extend(new_tokens) + token_to_idx_segment.extend([i_segment] * len(new_tokens)) + + next_seek = whisper_segments[i_segment+1]["seek"] if i_segment < len(whisper_segments) - 1 else None + if seek != next_seek: + start = float(seek * HOP_LENGTH / SAMPLE_RATE) + assert start < audio_duration, f"Got start {start} which is outside of audio duration {audio_duration}" + end = min(start + SEGMENT_DURATION, audio_duration) + tokens = current_tokens + + if tokens is None or not len(tokens): + continue + + start_sample = min(round(start * SAMPLE_RATE), audio.shape[-1]) + end_sample = min(round(end * SAMPLE_RATE), audio.shape[-1]) + + # Extract features on the audio segment + sub_audio = audio_minimum_padding(audio[start_sample:end_sample]) + + mfcc = whisper.log_mel_spectrogram(sub_audio, n_mels).to(model.device) + mfcc = whisper.pad_or_trim(mfcc, N_FRAMES) + mfcc = mfcc.unsqueeze(0) + + segment_tokens_check = [] + if tokens[0] >= tokenizer.timestamp_begin: + segment_tokens_check.append(tokens[0]) + while tokens[0] >= tokenizer.timestamp_begin: + tokens = tokens[1:] + assert len(tokens), "Got transcription with only timestamps!" + last_token_check = None + while tokens[-1] >= tokenizer.timestamp_begin: + last_token_check = tokens[-1] + tokens = tokens[:-1] + + sot_sequence = tokenizer.sot_sequence + if language and len(sot_sequence) == 3: + sot_sequence = ( + sot_sequence[0], + tokenizer.to_language_token(language), + sot_sequence[2], + ) + tokens = [ + *sot_sequence, + tokenizer.timestamp_begin, + ] + tokens + + i_start = len(sot_sequence) + + with torch.no_grad(): + logprobs = model(mfcc, torch.Tensor(tokens).int().to(model.device).unsqueeze(0)) + logprobs = F.log_softmax(logprobs, dim=-1) + + end_token = tokenizer.timestamp_begin + round(min(N_FRAMES * HOP_LENGTH, end_sample - start_sample) // AUDIO_SAMPLES_PER_TOKEN) + tokens = tokens[i_start:] + [end_token] + attention_weights = [w[:, :, i_start-1:, :] for w in attention_weights] + + ws = perform_word_alignment( + tokens, + attention_weights, + tokenizer, + use_space=use_space, + alignment_heads=alignment_heads, + remove_punctuation_from_words=remove_punctuation_from_words, + refine_whisper_precision_nframes=refine_whisper_precision_nframes, + detect_disfluencies=detect_disfluencies, + mfcc=mfcc, + plot=plot_word_alignment, + ) + + segment_logprobs = [] + i_token = 1 + + for word in ws: + + word["start"] = round(word["start"] + start, 2) + word["end"] = round(word["end"] + start, 2) + + if trust_whisper_timestamps: + word.update({"idx_segment": i_segment}) + else: + assert i_token < len(tokens) + assert not len(word["tokens_indices"]) or word["tokens_indices"][0] == tokens[i_token] + word.update({"idx_segment": token_to_idx_segment[i_token]}) + i_token += len(word["tokens"]) + while i_token < len(tokens) and tokens[i_token] >= tokenizer.timestamp_begin: + i_token += 1 + + tok_indices = word["tokens_indices"] + segment_tokens_check.extend(tok_indices) + + if compute_word_confidence: + tok = word["tokens"] + i_end = i_start + len(tok) + if include_punctuation_in_confidence: + while len(tok) > 1 and len(tok[-1]) and tok[-1][-1] in _punctuation: # Note: look at the last character of token, to take into account "...", "!!", etc. + tok = tok[:-1] + tok_indices = tok_indices[:-1] + word_logprobs = [logprobs[:, step, tok] for (step, tok) in zip(range(i_start, i_start + len(tok_indices)), tok_indices)] + i_start = i_end + if len(word_logprobs): + word_logprobs = torch.cat(word_logprobs) + segment_logprobs.append(word_logprobs) + word_confidence = word_logprobs.mean().exp().item() + else: + word_confidence = 0 + word.update({"confidence": round_confidence(word_confidence)}) + + words.append(word) + + if verbose: + print_timestamped(word) + + if last_token_check is not None: + segment_tokens_check.append(last_token_check) + if trust_whisper_timestamps: + if segment_tokens_check != segment["tokens"]: + assert len(segment_tokens_check) < len(segment["tokens"]), \ + f"First should be longer by one token: '{tokenizer.decode_with_timestamps(segment_tokens_check)}' should include '{tokenizer.decode_with_timestamps(segment['tokens'])}'" + assert segment_tokens_check[:-1] == segment["tokens"][:len(segment_tokens_check)-1], \ + f"Got inconsistent tokens: {tokenizer.decode_with_timestamps(segment_tokens_check)} != {tokenizer.decode_with_timestamps(segment['tokens'])}" + segment["tokens"] = segment_tokens_check + segment["text"] = tokenizer.decode(segment["tokens"]) + # else: TODO + + if len(segment_logprobs): + segment.update({"confidence": round_confidence(torch.cat(segment_logprobs).mean().exp().item())}) + + if len(ws): + previous_end = ws[-1]["end"] + + if not trust_whisper_timestamps: + current_tokens = [] + token_to_idx_segment = [] + + finally: + + # Remove hooks + for hook in all_hooks: + hook.remove() + + if language_probs: + transcription["language_probs"] = language_probs + + return (transcription, words) + +def get_audio_tensor(audio, device="cpu"): + if isinstance(audio, str): + audio = whisper.load_audio(audio) + if isinstance(audio, np.ndarray): + audio = torch.Tensor(audio) + else: + assert isinstance(audio, torch.Tensor), f"Got unexpected audio of type {type(audio)}" + return audio.to(device) + +def audio_minimum_padding(audio): + if audio.shape[-1] <= 200: + return whisper.pad_or_trim(audio, 201) + return audio + + +def should_use_space(language): + return norm_language(language) not in ["zh", "ja", "th", "lo", "my", "yue"] + +def norm_language(language): + if language is None: + return "en" + return whisper.tokenizer.TO_LANGUAGE_CODE.get(language.lower(), language) + +def print_timestamped(w): + line = f"[{format_timestamp(w['start'])} --> {format_timestamp(w['end'])}] {w['text']}\n" + # compared to just `print(line)`, this replaces any character not representable using + # the system default encoding with an '?', avoiding UnicodeEncodeError. + sys.stdout.write(line.encode(sys.getdefaultencoding(), errors="replace").decode()) + sys.stdout.flush() + + +def get_logit_filters(model, whisper_options, prompt = None): + if is_transformer_model(model): + # import transformers + # transformers.WhisperTimeStampLogitsProcessor + raise NotImplementedError("TODO") + decoding_options = get_decoding_options(whisper_options) + if "initial_prompt" in decoding_options: + prompt0 = decoding_options.pop("initial_prompt") + if prompt is None: + prompt = prompt0 + if prompt is not None: + decoding_options["prompt"] = prompt + decoding_options = whisper.DecodingOptions( + without_timestamps=False, + max_initial_timestamp=1.0, + prefix=None, + suppress_blank=True, + **decoding_options + ) + + # This performs some checks on the options + decoding_task = whisper.decoding.DecodingTask(model, decoding_options) + return decoding_task.logit_filters + +def get_decoding_options(whisper_options): + return dict([(k,v) for (k,v) in whisper_options.items() + if k not in [ + "no_speech_threshold", + "logprob_threshold", + "compression_ratio_threshold", + "condition_on_previous_text", + "verbose", + ] + ]) + +def get_tokenizer(model, task="transcribe", language="en"): + if is_transformer_model(model): + tokenizer = model.tokenizer + tokenizer.sot_sequence = ( + tokenizer.sot, + tokenizer.to_language_token(language or "en"), + tokenizer.to_task_token(task), + ) + tokenizer.sot_sequence + return model.tokenizer + try: + return whisper.tokenizer.get_tokenizer( + model.is_multilingual, + num_languages=model.num_languages if hasattr(model, "num_languages") else 99, + task=task, language=language + ) + except TypeError: # Old openai-whisper version + return whisper.tokenizer.get_tokenizer( + model.is_multilingual, + task=task, language=language + ) + +def perform_word_alignment( + tokens, + attention_weights, + tokenizer, + use_space=True, + mfcc=None, + refine_whisper_precision_nframes=0, + remove_punctuation_from_words=False, + include_punctuation_in_timing=False, # Was True before 1.9 + unfinished_decoding=False, + alignment_heads=None, + medfilt_width=9, + qk_scale=1.0, + detect_disfluencies=True, + subwords_can_be_empty=True, # Was False before 1.11 + plot=False, + debug=False, +): + """ + Perform word alignment on the given tokens and attention weights. + Returns a list of (word, start_time, end_time) tuples. + + tokens: list of tokens (integers) + attention_weights: list of attention weights (torch tensors) + tokenizer: tokenizer used to tokenize the text + use_space: whether to use spaces to split the tokens into words (should be true for all languages except Japanese, Chinese, ...) + mfcc: MFCC features (used to identify padded region, and for plotting) + refine_whisper_precision_nframes: precision time + remove_punctuation_from_words: whether to remove punctuation from words + include_punctuation_in_timing: whether to include punctuation in the timing of (previous) words + unfinished_decoding: whether the decoding is unfinished (e.g. because the model is stuck) + alignment_heads: list of attention heads to use for alignment + medfilt_width: width of the median filter used to smooth the attention weights + qk_scale: scale factor applied to the attention weights + plot: whether to plot the word alignment + debug: whether to print debug information + """ + + assert len(tokens) > 1, f"Got unexpected sequence of tokens of length {len(tokens)} {tokenizer.decode_with_timestamps(tokens)}" + start_token = tokens[0] - tokenizer.timestamp_begin + end_token = tokens[-1] - tokenizer.timestamp_begin + + # Check start / end tokens + if start_token < 0: + raise RuntimeError(f"Missing start token in: {tokenizer.decode_with_timestamps(tokens)}") + if len(tokens) == 1 or end_token < 0: + # This can happens when Whisper is stucked as a Language Model + if debug: + logger.debug(f"Missing end token in {tokenizer.decode_with_timestamps(tokens)}") + end_token = N_FRAMES // 2 + if end_token == start_token and refine_whisper_precision_nframes == 0: + if debug: + logger.debug(f"Got empty segment in {tokenizer.decode_with_timestamps(tokens)}") + return [] + + # Let a minimal duration given the number of tokens (see https://github.com/linto-ai/whisper-timestamped/issues/67) + end_token = min(N_FRAMES // 2, max(end_token, start_token + len(tokens))) + + # Put some margin around the segment + if refine_whisper_precision_nframes > 0: + start_token = max(start_token - refine_whisper_precision_nframes, 0) + end_token = min(end_token + refine_whisper_precision_nframes, N_FRAMES // 2) + + if end_token <= start_token: + raise RuntimeError(f"Got segment with null or negative duration {tokenizer.decode_with_timestamps(tokens)}: {start_token} {end_token}") + + start_time = start_token * AUDIO_TIME_PER_TOKEN + # end_time = end_token * AUDIO_TIME_PER_TOKEN + + split_tokens = split_tokens_on_spaces if use_space else split_tokens_on_unicode + words, word_tokens, word_tokens_indices = split_tokens(tokens, tokenizer, remove_punctuation_from_words=remove_punctuation_from_words) + + # If the last token is a punctuation that comes after a word + # group this final punctuation with the final timestamp + # This is to avoid assigning the final punctuation to a big silence or a noise/music background coming after + num_punctuations_per_tokens = [ + 0 if len(w) == 1 or w[-1] not in _punctuation else 1 + for w in word_tokens + ] + if include_punctuation_in_timing: + num_punctuations_per_tokens[:-2]=[0]*(len(num_punctuations_per_tokens)-2) + + for i, w in enumerate(attention_weights): + assert w.shape[-2] == len(tokens), f"Attention weights have wrong shape: {w.shape[-2]} (expected {len(tokens)})." + weights = torch.cat(attention_weights) # layers * heads * tokens * frames + + num_tokens = weights.shape[-2] + num_frames = end_token - start_token + if num_tokens > num_frames: + logger.warning(f"Too much text ({num_tokens} tokens) for the given number of frames ({num_frames}) in: {tokenizer.decode_with_timestamps(tokens)}\nThe end of the text will be removed.") + return perform_word_alignment( + tokens[:num_frames-1] + [tokens[-1]], + [torch.cat([w[:, :, :num_frames-1, :], w[:, :, -1:, :]], dim=-2) + for w in attention_weights], + tokenizer, + use_space=use_space, + refine_whisper_precision_nframes=refine_whisper_precision_nframes, + medfilt_width=medfilt_width, + qk_scale=qk_scale, + alignment_heads=alignment_heads, + mfcc=mfcc, + plot=plot, + remove_punctuation_from_words=remove_punctuation_from_words, + detect_disfluencies=detect_disfluencies, + subwords_can_be_empty=subwords_can_be_empty, + unfinished_decoding=True, + debug=debug, + ) + + assert end_token <= weights.shape[-1] + assert len(tokens) == num_tokens + + weights = weights[..., start_token: end_token].cpu() # layers * heads * tokens * frames + + if alignment_heads is None: + weights = weights.reshape(-1, *weights.shape[-2:]) # N * tokens * frames + else: + weights = torch.stack([weights[l][h] for l, h in alignment_heads.indices().T]) + weights = median_filter(weights, (1, 1, medfilt_width)) + weights = torch.tensor(weights * qk_scale).softmax(dim=-1) + weights = weights.mean(axis=(0)) # average over layers and heads # tokens * frames + weights = weights / weights.norm(dim=-2, keepdim=True) # This was before the mean before 1.9 + weights = -weights.double().numpy() + worse_weight = 0 + + # Get the limit of audio duration + max_duration = None + if mfcc is not None: + max_duration = find_start_padding(mfcc) + if max_duration is not None: + max_duration = max_duration // 2 + + # Enforce the max duration + if max_duration: + if start_token >= max_duration: + logger.warning(f"Got start time outside of audio boundary") + else: + weights[:-1, max_duration:] = worse_weight + + # Encourage to start early + weights[0, 0] = weights.min() + # weights[0, refine_whisper_precision_nframes*2:] = worse_weight + + if subwords_can_be_empty: + step_pattern = dtw.stepPattern.symmetric1 + else: + # Similar as "symmetric1" but without the possibility to have the same timestamp for two tokens + step_pattern = dtw.stepPattern.StepPattern(dtw.stepPattern._c( + 1, 1, 1, -1, + 1, 0, 0, 1, + 2, 0, 1, -1, + 2, 0, 0, 1, + )) + alignment = dtw.dtw(weights, step_pattern=step_pattern) + + global num_alignment_for_plot + num_alignment_for_plot += 1 + + if plot: + import matplotlib.pyplot as plt + import matplotlib.ticker as ticker + + plot_mfcc = 1 if mfcc is not None else 0 + plot_disfluencies = 1 if detect_disfluencies else 0 + nplots = (1 + plot_mfcc + plot_disfluencies) + + plt.subplots(nplots, 1, figsize=(16, 9), gridspec_kw={'height_ratios': [3] + [1] * (nplots - 1)}) + plt.subplot(nplots, 1, 1, frameon=False) + + plt.imshow(-weights, aspect="auto") + plt.plot(alignment.index2s, alignment.index1s, color="red") + + xticks = np.arange(0, weights.shape[1], 1 / AUDIO_TIME_PER_TOKEN) + xticklabels = [round_timestamp(x) for x in xticks * AUDIO_TIME_PER_TOKEN + start_time] + + ylims = plt.gca().get_ylim() + + ax = plt.gca() + ax.tick_params('both', length=0, width=0, which='minor', pad=6) + + ax.yaxis.set_ticks_position("left") + ax.yaxis.set_label_position("left") + ax.invert_yaxis() + ax.set_ylim(ylims) + + major_ticks = [-0.5] + minor_ticks = [] + current_y = 0 + + for word, word_token in zip(words, word_tokens): + minor_ticks.append(current_y + len(word_token) / 2 - 0.5) + current_y += len(word_token) + major_ticks.append(current_y - 0.5) + + words_with_subwords = ["|".join(s).strip() for (w, s) in zip(words, word_tokens)] + + ax.yaxis.set_minor_locator(ticker.FixedLocator(minor_ticks)) + ax.yaxis.set_minor_formatter( + ticker.FixedFormatter(words_with_subwords)) + ax.set_yticks(major_ticks) + ax.yaxis.set_major_formatter(ticker.NullFormatter()) + for y in major_ticks: + plt.axhline(y, color="black", linestyle="dashed") + + plt.ylabel("Words") + + if plot_mfcc: + plt.xticks(xticks) + plt.setp(plt.gca().get_xticklabels(), visible=False) + + xticks *= 2 + + plt.subplot(nplots, 1, 2, frameon=False) + plt.imshow(mfcc[0, :, start_token * 2: end_token * 2].cpu(), aspect="auto", origin="lower") + plt.yticks([]) + plt.ylabel("MFCC") + + plt.xticks(xticks, xticklabels) + plt.xlabel("Time (s)") + + jumps = np.diff(alignment.index1s) + jumps = np.pad(jumps, (1, 0), constant_values=1) + jumps = jumps.astype(bool) + jumps = alignment.index2s[jumps] + jumps = np.pad(jumps, (0, 1), constant_values=alignment.index2s[-1]) + + jumps_start = jumps + disfluences = {} + if detect_disfluencies: + jumps_start = copy.copy(jumps) + + for (i_token, (tok, begin, end)) in enumerate(zip(tokens, jumps[:-1], jumps[1:])): + + # Find local maxima in the portion of attention weights + attention_weights = -weights[i_token, begin:end] + peaks, properties = find_peaks(attention_weights, + width=3, + prominence=0.02, + ) + # If more than + if len(peaks) > 1: + if "left_ips" in properties: + left = [round(x) for x in properties["left_ips"]] + else: + left = properties["left_bases"] + + new_begin = left[-1] + begin + + jumps_start[i_token] = new_begin + + if new_begin != begin: + is_punctuation = tokenizer.decode_with_timestamps([tok]) in _punctuation + if not is_punctuation: + disfluences[i_token] = (begin, jumps_start[i_token]) + else: + disfluences[i_token+1] = (begin, end) + + if plot: + plt.subplot(nplots, 1, 2 + plot_mfcc, frameon=False) + plt.plot(range(begin,end), attention_weights) + plt.xlim(0, end) + + for i, p in enumerate(peaks): + color = 'red' if (len(peaks)>1 and i1 else 'green' + barxxy(begin+properties["left_bases"], begin+properties["right_bases"], properties.get("prominences",[1]*len(properties["left_bases"])), alpha=0.5, + # put a line with a custom color + linewidth=1, edgecolor=color + ) + if "left_ips" in properties: + for left in properties["left_ips"]: + plt.vlines(begin+left, 0, 0.5, color='green', linestyle=':') + for right in properties["right_ips"]: + plt.vlines(begin+right, 0, 0.5, color='red', linestyle=':') + + + # display the word-level timestamps in a table + word_boundaries = np.cumsum([len(t) for t in word_tokens]) + word_boundaries = np.pad(word_boundaries, (1, 0)) + begin_times = jumps_start[word_boundaries[:-1]] + end_times = jumps[word_boundaries[1:] - num_punctuations_per_tokens] + + begin_times = begin_times * AUDIO_TIME_PER_TOKEN + end_times = end_times * AUDIO_TIME_PER_TOKEN + + if detect_disfluencies: + to_be_added = [] + i_start = 0 + for i_word, toks in enumerate(word_tokens[:-1]): + i_end = i_start + len(toks) + if i_start in disfluences and i_word > 0: + begin, end = disfluences[i_start] + begin *= AUDIO_TIME_PER_TOKEN + end *= AUDIO_TIME_PER_TOKEN + to_be_added.append((i_word, begin, end)) + i_start = i_end + # Add from the end to avoid messing up the indices + for (i_word, begin, end) in to_be_added[-1::-1]: + words.insert(i_word, DISFLUENCY_MARK) + word_tokens.insert(i_word, []) + word_tokens_indices.insert(i_word, []) + begin_times = np.insert(begin_times, i_word, begin) + end_times = np.insert(end_times, i_word, end) + + # Ignore start / end tokens + if not refine_whisper_precision_nframes: + begin_times[1] = begin_times[0] + if not refine_whisper_precision_nframes: + end_times[-2] = end_times[-1] + if unfinished_decoding: + words = words[1:] + word_tokens = word_tokens[1:] + word_tokens_indices = word_tokens_indices[1:] + begin_times = begin_times[1:] + end_times = end_times[1:] + else: + words = words[1:-1] + word_tokens = word_tokens[1:-1] + word_tokens_indices = word_tokens_indices[1:-1] + begin_times = begin_times[1:-1] + end_times = end_times[1:-1] + + if plot: + ymin = 1 + + plt.subplot(nplots, 1, 1) + for i, (w, ws, begin, end) in enumerate(zip(words, word_tokens, begin_times, end_times)): + ymax = ymin + len(ws) + if mfcc is None: + plt.text(begin / AUDIO_TIME_PER_TOKEN, num_tokens-0.5, w, ha="left", va="top", color="red") + for x in [begin, end,]: + plt.axvline(x / AUDIO_TIME_PER_TOKEN, color="red", linestyle="dotted", + ymin=1-ymin/num_tokens, + ymax=0, # 1-ymax/num_tokens, + ) + ymin = ymax + + if plot_mfcc: + plt.subplot(nplots, 1, 2) + for i, (w, begin, end) in enumerate(zip(words, begin_times, end_times)): + plt.text(begin * 2 / AUDIO_TIME_PER_TOKEN, mfcc.shape[-2]*1.05, w, ha="left", va="bottom", color="red") + for x in [begin, end,]: + plt.axvline(x * 2 / AUDIO_TIME_PER_TOKEN, color="red", linestyle="dotted") + + if isinstance(plot, str): + plt.savefig(f"{plot}.alignment{num_alignment_for_plot:03d}.jpg", bbox_inches='tight', pad_inches=0) + else: + plt.show() + + return [ + dict( + text=word, + start=round_timestamp(begin + start_time), + end=round_timestamp(end + start_time), + tokens=tokens, + tokens_indices=tokens_indices, + ) + for word, begin, end, tokens, tokens_indices in zip(words, begin_times, end_times, word_tokens, word_tokens_indices) + if not word.startswith("<|") + ] + +def find_start_padding(mfcc): + """ Return start of padding given the mfcc, or None if there is no padding """ + last_mfcc = mfcc[0, :, -1] + if torch.min(last_mfcc) == torch.max(last_mfcc) == 0: + candidate_index = mfcc.shape[-1] - 2 + while candidate_index > 0: + candidate = mfcc[0, :, candidate_index] + if not torch.equal(candidate, last_mfcc): + return candidate_index + 1 + candidate_index -= 1 + return 0 # WTF!? + +def round_confidence(x): + return round(x, 3) + +def round_timestamp(x): + return round(x, 2) + +_punctuation = "".join(c for c in string.punctuation if c not in ["-", "'"]) + "。，！？：”、…" + +def split_tokens_on_unicode(tokens: list, tokenizer, remove_punctuation_from_words=False, isolate_punctuations=False): + words = [] + word_tokens = [] + word_tokens_indices = [] + current_tokens = [] + + for token in tokens: + current_tokens.append(token) + decoded = tokenizer.decode_with_timestamps([t for t in current_tokens if t < tokenizer.eot or t >= tokenizer.timestamp_begin]) + if "\ufffd" not in decoded: + empty_tokens = [""] * (len(current_tokens)-1) + punctuation = not isolate_punctuations and (decoded.strip() and decoded.strip() in _punctuation) + previous_special = len(word_tokens_indices) > 0 and (word_tokens_indices[-1][-1] >= tokenizer.timestamp_begin) + if punctuation and not previous_special: + if len(words) == 0: + words = [""] + word_tokens = [[]] + if not remove_punctuation_from_words: + words[-1] += decoded + word_tokens[-1].extend(empty_tokens + [decoded]) + word_tokens_indices[-1].extend(current_tokens) + else: + words.append(decoded) + word_tokens.append(empty_tokens + [decoded]) + word_tokens_indices.append(current_tokens) + current_tokens = [] + + return words, word_tokens, word_tokens_indices + + +def split_tokens_on_spaces(tokens: torch.Tensor, tokenizer, remove_punctuation_from_words=False): + subwords, subword_tokens_list, subword_tokens_indices_list = split_tokens_on_unicode(tokens, tokenizer, remove_punctuation_from_words=remove_punctuation_from_words) + words = [] + word_tokens = [] + word_tokens_indices = [] + + for i, (subword, subword_tokens, subword_tokens_indices) in enumerate(zip(subwords, subword_tokens_list, subword_tokens_indices_list)): + special = (subword_tokens_indices[0] >= tokenizer.timestamp_begin) + previous_special = (i > 0) and (subword_tokens_indices_list[i-1][0] >= tokenizer.timestamp_begin) + next_special = (i < len(subword_tokens_indices_list)-1) and (subword_tokens_indices_list[i+1][0] >= tokenizer.timestamp_begin) + previous_space = (i > 0) and (not subwords[i-1].strip()) + is_space = not subword.strip() + with_space = subword.startswith(" ") and not is_space + punctuation = not is_space and subword.strip() in _punctuation + if special or (not previous_space and (previous_special or (with_space and not punctuation) or (is_space and not next_special))): + words.append(subword.strip()) + word_tokens.append(subword_tokens) + word_tokens_indices.append(subword_tokens_indices) + else: + words[-1] = words[-1] + subword.strip() + word_tokens[-1].extend(subword_tokens) + word_tokens_indices[-1].extend(subword_tokens_indices) + + return words, word_tokens, word_tokens_indices + +def check_vad_method(method, with_version=False): + """ + Check whether the VAD method is valid and return the method in a consistent format + + method: str or list or True or False + """ + if method in [True, "True", "true"]: + return check_vad_method("silero") # default method + elif method in [None, False, "False", "false", "None", "none"]: + return None + elif not isinstance(method, str) and hasattr(method, '__iter__'): + # list of explicit timestamps + checked_pairs = [] + for s_e in method: + assert len(s_e) == 2, f"Got unexpected element {s_e} in the list of VAD segments. Expect (start, end) pairs" + checked_pairs.append(tuple(s_e)) + return checked_pairs + elif isinstance(method, str) and method.startswith("silero"): + version = None + if method != "silero": + assert method.startswith("silero:"), f"Got unexpected VAD method {method}" + version = method.split(":")[1] + if not version.startswith("v"): + version = "v" + version + try: + assert float(version[1:]) >= 1 + except: + raise ValueError(f"Got unexpected silero version {version} (please check https://github.com/snakers4/silero-vad/wiki/Version-history-and-Available-Models)") + if with_version: + return ("silero", version) + else: + return method + elif method == "auditok": + try: + import auditok + except ImportError: + raise ImportError("Please install auditok to use the auditok VAD (or use another VAD method)") + else: + try: + method = eval(method) + assert hasattr(method, '__iter__') + except: + raise ValueError(f"Got unexpected VAD method {method}") + return check_vad_method(method, with_version=with_version) + return method + +_silero_vad_model = {} +_has_onnx = None +def get_vad_segments(audio, + sample_rate=SAMPLE_RATE, + output_sample=False, + min_speech_duration=0.1, + min_silence_duration=0.1, + dilatation=0.5, + method="silero", + ): + """ + Get speech segments from audio using Silero VAD + parameters: + audio: torch.Tensor + audio data *in 16kHz* + output_sample: bool + if True, return start and end in samples instead of seconds + min_speech_duration: float + minimum duration (in sec) of a speech segment + min_silence_duration: float + minimum duration (in sec) of a silence segment + dilatation: float + how much (in sec) to enlarge each speech segment detected by the VAD + method: str or list + VAD method to use (auditok, silero, silero:v3.1) + """ + global _silero_vad_model, _silero_get_speech_ts, _has_onnx + + if isinstance(method, list): + # Explicit timestamps + segments = [{"start": s * sample_rate, "end": e * sample_rate} for (s, e) in method] + dilatation = 0 + + elif isinstance(method, str) and method.startswith("silero"): + + version = None + _, version = check_vad_method(method, True) + # See discussion https://github.com/linto-ai/whisper-timestamped/pull/142/files#r1398326287 + need_folder_hack = version and (version < "v4") + + if _silero_vad_model.get(version) is None: + # ONNX support since 3.1 in silero + if (version is None or version >= "v3.1") and (_has_onnx is not False): + onnx=True + try: + import onnxruntime + onnxruntime.set_default_logger_severity(3) # Remove warning "Removing initializer 'XXX'. It is not used by any node and should be removed from the model." + _has_onnx = True + except ImportError as err: + logger.warning(f"Please install onnxruntime to use more efficiently silero VAD") + _has_onnx = False + onnx=False + else: + onnx=False + + # Choose silero version because of problems with version 4, see https://github.com/linto-ai/whisper-timestamped/issues/74 + torch_home = os.environ.get('TORCH_HOME', '~/.cache/torch') + repo_or_dir_master = os.path.expanduser(torch_home + "/hub/snakers4_silero-vad_master") + repo_or_dir_specific = os.path.expanduser(torch_home + f"/hub/snakers4_silero-vad_{version}") if version else repo_or_dir_master + repo_or_dir = repo_or_dir_specific + tmp_folder = None + def apply_folder_hack(): + nonlocal tmp_folder + if os.path.exists(repo_or_dir_master): + tmp_folder = repo_or_dir_master + ".tmp" + shutil.move(repo_or_dir_master, tmp_folder) + # Make a symlink to the v3.1 model, otherwise it fails + input_exists = os.path.exists(repo_or_dir_specific) + if not input_exists: + # Make dummy file for the symlink to work + os.makedirs(repo_or_dir_specific, exist_ok=True) + os.symlink(repo_or_dir_specific, repo_or_dir_master) + if not input_exists: + shutil.rmtree(repo_or_dir_specific) + + source = "local" + if not os.path.exists(repo_or_dir): + # Load specific version of silero + repo_or_dir = f"snakers4/silero-vad:{version}" if version else "snakers4/silero-vad" + source = "github" + if need_folder_hack: + apply_folder_hack() + try: + silero_vad_model, utils = torch.hub.load(repo_or_dir=repo_or_dir, model="silero_vad", onnx=onnx, source=source) + _silero_vad_model[version] = silero_vad_model + except ImportError as err: + raise RuntimeError(f"Please install what is needed to use the silero VAD (or use another VAD method)") from err + except Exception as err: + raise RuntimeError(f"Problem when installing silero with version {version}. Check versions here: https://github.com/snakers4/silero-vad/wiki/Version-history-and-Available-Models") from err + finally: + if need_folder_hack: + if os.path.exists(repo_or_dir_master): + os.remove(repo_or_dir_master) + if tmp_folder: + shutil.move(tmp_folder, repo_or_dir_master) + assert os.path.isdir(repo_or_dir_specific), f"Unexpected situation: missing {repo_or_dir_specific}" + + _silero_get_speech_ts = utils[0] + + # Cheap normalization of the volume + audio = audio / max(0.1, audio.abs().max()) + + segments = _silero_get_speech_ts(audio, _silero_vad_model[version], + sampling_rate = sample_rate, + min_speech_duration_ms = round(min_speech_duration * 1000), + min_silence_duration_ms = round(min_silence_duration * 1000), + return_seconds = False, + ) + + elif method == "auditok": + import auditok + + # Cheap normalization of the volume + audio = audio / max(0.1, audio.abs().max()) + + data = (audio.numpy() * 32767).astype(np.int16).tobytes() + + audio_duration = len(audio) / sample_rate + + segments = auditok.split( + data, + sampling_rate=sample_rate, # sampling frequency in Hz + channels=1, # number of channels + sample_width=2, # number of bytes per sample + min_dur=min_speech_duration, # minimum duration of a valid audio event in seconds + max_dur=audio_duration, # maximum duration of an event + max_silence=min(audio_duration*.95, min_silence_duration), # maximum duration of tolerated continuous silence within an event + energy_threshold=50, + drop_trailing_silence=True, + ) + + segments = [{"start": s._meta.start * sample_rate, "end": s._meta.end * sample_rate} for s in segments] + + else: + raise ValueError(f"Got unexpected VAD method {method}") + + if dilatation > 0: + dilatation = round(dilatation * sample_rate) + new_segments = [] + for seg in segments: + new_seg = { + "start": max(0, seg["start"] - dilatation), + "end": min(len(audio), seg["end"] + dilatation) + } + if len(new_segments) > 0 and new_segments[-1]["end"] >= new_seg["start"]: + new_segments[-1]["end"] = new_seg["end"] + else: + new_segments.append(new_seg) + segments = new_segments + + ratio = 1 if output_sample else 1 / sample_rate + + if ratio != 1: + for seg in segments: + seg["start"] *= ratio + seg["end"] *= ratio + if output_sample: + for seg in segments: + seg["start"] = round(seg["start"]) + seg["end"] = round(seg["end"]) + return segments + +def remove_non_speech(audio, + use_sample=False, + min_speech_duration=0.1, + min_silence_duration=1, + dilatation=0.5, + sample_rate=SAMPLE_RATE, + method="silero", + avoid_empty_speech=False, + plot=False, + ): + """ + Remove non-speech segments from audio (using Silero VAD), + glue the speech segments together and return the result along with + a function to convert timestamps from the new audio to the original audio + + parameters: + audio: torch.Tensor + audio data *in 16kHz* + use_sample: bool + if True, return start and end in samples instead of seconds + min_speech_duration: float + minimum duration (in sec) of a speech segment + min_silence_duration: float + minimum duration (in sec) of a silence segment + dilatation: float + how much (in sec) to enlarge each speech segment detected by the VAD + method: str + method to use to remove non-speech segments + avoid_empty_speech: bool + if True, avoid returning an empty speech segment (re) + plot: bool or str + if True, plot the result. + If a string, save the plot to the given file + """ + + segments = get_vad_segments( + audio, + sample_rate=sample_rate, + output_sample=True, + min_speech_duration=min_speech_duration, + min_silence_duration=min_silence_duration, + dilatation=dilatation, + method=method, + ) + + segments = [(seg["start"], seg["end"]) for seg in segments] + if len(segments) == 0: + if avoid_empty_speech: + segments = [(0, audio.shape[-1])] + else: + return torch.Tensor([]), [], lambda t, t2 = None: t if t2 is None else [t, t2] + + audio_speech = torch.cat([audio[..., s:e] for s,e in segments], dim=-1) + + if plot: + import matplotlib.pyplot as plt + plt.figure() + max_num_samples = 10000 + step = (audio.shape[-1] // max_num_samples) + 1 + times = [i*step/sample_rate for i in range((audio.shape[-1]-1) // step + 1)] + plt.plot(times, audio[::step]) + for s, e in segments: + plt.axvspan(s/sample_rate, e/sample_rate, color='red', alpha=0.1) + if isinstance(plot, str): + plt.savefig(f"{plot}.VAD.jpg", bbox_inches='tight', pad_inches=0) + else: + plt.show() + + if not use_sample: + segments = [(float(s)/sample_rate, float(e)/sample_rate) for s,e in segments] + + return audio_speech, segments, lambda t, t2 = None: do_convert_timestamps(segments, t, t2) + +def do_convert_timestamps(segments, t, t2 = None): + """ + Convert timestamp from audio without non-speech segments to original audio (with non-speech segments) + + parameters: + segments: list of tuple (start, end) corresponding to non-speech segments in original audio + t: timestamp to convert + t2: second timestamp to convert (optional), when the two timestamps should be in the same segment + """ + assert len(segments) + ioffset = 0 # Input offset + ooffset = 0 # Output offset + ipreviousend = 0 + result = [] + for istart, iend in segments: + ostart = ooffset + oend = ostart + (iend - istart) + ooffset = oend + ioffset += istart - ipreviousend + ipreviousend = iend + t_in = t <= oend + t2_in = t_in if t2 is None else t2 <= oend + if t_in or t2_in: + result.append([ + max(istart, min(iend, ioffset + t)), + max(istart, min(iend, ioffset + t2)) if t2 is not None else None + ]) + if t_in and t2_in: + break + if not len(result): + result.append( + [ioffset + t, ioffset + t2 if t2 is not None else None] + ) + + if len(result) > 1: + # Minimize difference between durations + result = sorted(result, key=lambda x: abs(abs(t2-t) - abs(x[1]-x[0]))) + result = result[0] + if t2 is None: + result = round(result[0], 2) + else: + result = [round(x, 2) for x in result] + return result + +def remove_last_null_duration_words(transcription, words, recompute_text=False): + """ + Remove words with null duration happening at the end of a chunk (probable Whisper hallucinations) + """ + # First group segments by audio chunk + segments_groups = {} + seek = None + current_chunk = -1 + for i, segment in enumerate(transcription["segments"]): + if segment["seek"] != seek: + current_chunk += 1 + seek = segment["seek"] + segments_groups[i] = current_chunk + + # Remove words with null duration happening at the end of a chunk + current_chunk = -1 + is_last_empty = False + to_remove = [] + for i, word in enumerate(words[::-1]): # Reverse order + i = len(words) - i - 1 + empty = (word["start"] == word["end"]) + idx_segment = word["idx_segment"] + group = segments_groups[idx_segment] + if current_chunk != group: + is_last_empty = empty + current_chunk = group + elif not empty: + is_last_empty = False + if is_last_empty: + # Remove word + to_remove.append(i) + # Shorten text of segment + full_word = "".join(word["tokens"]) + logger.debug(f"Removing word {i+1}/{len(words)} \"{full_word}\" with empty duration at the end of segment {idx_segment+1}/{len(transcription['segments'])}") + segment = transcription["segments"][idx_segment] + text = segment["text"] + if not text.endswith(full_word): # see issue #62 + if text.endswith(full_word[:-1]): + full_word = full_word[:-1] + elif text[:-1].endswith(full_word): + text = text[:-1] + else: + raise RuntimeError(f"\"{text}\" not ending with \"{full_word}\"") + text = text[:-len(full_word)] + if i > 0 and words[i-1]["idx_segment"] == idx_segment: + segment["text"] = text + else: + logger.debug(f"Removing empty segment {idx_segment}") + # Remove segment with no more words + transcription["segments"].pop(idx_segment) + for j in range(i+1, len(words)): + words[j]["idx_segment"] -= 1 + recompute_text = True + + for i in to_remove: + words.pop(i) # Warning: inplace modification + + if recompute_text: + transcription["text"] = "".join([s["text"] for s in transcription["segments"]]) + + return transcription, words + + +def ensure_increasing_positions(segments, min_duration=0): + """ + Ensure that "start" and "end" come in increasing order + """ + has_modified_backward = False + previous_end = 0 + for i, seg in enumerate(segments): + if seg["start"] < previous_end: + assert i > 0 + new_start = round_timestamp((previous_end + seg["start"]) / 2) + if new_start < segments[i-1]["start"] + min_duration: + new_start = previous_end + else: + segments[i-1]["end"] = new_start + has_modified_backward = True + seg["start"] = new_start + if seg["end"] <= seg["start"] + min_duration: + seg["end"] = seg["start"] + min_duration + previous_end = seg["end"] + if has_modified_backward: + return ensure_increasing_positions(segments, min_duration) + + previous_end = 0 + for seg in segments: + seg["start"] = round_timestamp(seg["start"]) + seg["end"] = round_timestamp(seg["end"]) + assert seg["start"] >= previous_end, f"Got segment {seg} coming before the previous finishes ({previous_end} > {seg['start']})" + assert seg["end"] >= seg["start"], f"Got segment {seg} with end < start" + previous_end = seg["end"] + + return segments + +## Some utilities for writing transcripts to files + +def flatten(list_of_lists, key = None): + for sublist in list_of_lists: + for item in sublist.get(key, []) if key else sublist: + yield item + +def remove_keys(list_of_dicts, key): + for d in list_of_dicts: + yield {k: d[k] for k in d.keys() - {key}} + + +def write_csv(transcript, file, sep = ",", text_first=True, format_timestamps=None, header=False): + writer = csv.writer(file, delimiter=sep) + if format_timestamps is None: format_timestamps = lambda x: x + if header is True: + header = ["text", "start", "end"] if text_first else ["start", "end", "text"] + if header: + writer.writerow(header) + if text_first: + writer.writerows( + [[segment["text"].strip(), format_timestamps(segment["start"]), format_timestamps(segment["end"])] for segment in transcript] + ) + else: + writer.writerows( + [[format_timestamps(segment["start"]), format_timestamps(segment["end"]), segment["text"].strip()] for segment in transcript] + ) + +# https://stackoverflow.com/questions/66588715/runtimeerror-cudnn-error-cudnn-status-not-initialized-using-pytorch +# CUDA initialization may fail on old GPU card +def force_cudnn_initialization(device=None, s=32): + if device is None: + device = get_default_device() + torch.nn.functional.conv2d(torch.zeros(s, s, s, s, device=device), torch.zeros(s, s, s, s, device=device)) + +def get_default_device(): + if torch.cuda.is_available(): + device = "cuda" + elif find_spec('torch.xpu') is not None and torch.xpu.is_available(): + device = "xpu" + else: + device = "cpu" + return device + +# base85-encoded (n_layers, n_heads) boolean arrays indicating the cross-attention heads that are +# highly correlated to the word-level timing, i.e. the alignment between audio and text tokens. +_ALIGNMENT_HEADS = { + "tiny.en": b"ABzY8J1N>@0{>%R00Bk>$p{7v037`oCl~+#00", + "tiny": b"ABzY8bu8Lr0{>%RKn9Fp%m@SkK7Kt=7ytkO", + "base.en": b"ABzY8;40c<0{>%RzzG;p*o+Vo09|#PsxSZm00", + "base": b"ABzY8KQ!870{>%RzyTQH3`Q^yNP!>##QT-?_)10{>%RpeA61k&I|OI3I$65C{;;pbCHh0B{qLQ;+}v00", + "small": b"ABzY8DmU6=0{>%Rpa?J`kvJ6qF(V^F86#Xh7JUGMK}P%R7%R7}kK1fFL7w6%<-Pf*t^=N)Qr&0RR9", + "large-v1": b"ABzY8r9j$a0{>%R7#4sLmoOs{s)o3~84-RPdcFk!JR%R7=D0pU<_bnWW*tkYAhobTNnu$jnkEkXqp)j;w1Tzk)UH3X%SZd&fFZ2fC2yj', + "large-v3": b"ABzY8gWO1E0{>%R7(9S+Kn!D~%ngiGaR?*L!iJG9p-nab0JQ=-{D1-g00", +} + +_PARAMETERS_TO_MODEL_NAME = { + 37184256 : "tiny.en", + 37184640 : "tiny", + 71825408 : "base.en", + 71825920 : "base", + 240582144 : "small.en", + 240582912 : "small", + 762320896 : "medium.en", + 762321920 : "medium", + 1541384960 : "large", + 1541570560 : "large-v3", +} + +def get_alignment_heads(model, max_top_layer=3): + if hasattr(model, "alignment_heads"): # Since version 20230306 + return model.alignment_heads + num_parameters = _get_number_of_parameters(model) + num_layers = model.dims.n_text_layer + num_heads = model.dims.n_text_head + if num_parameters not in _PARAMETERS_TO_MODEL_NAME: + logger.warning("Could not retrieve alignment heads : taking all attention heads from the top layers") + return None + model_name = _PARAMETERS_TO_MODEL_NAME[num_parameters] + if model_name == "large": + if next(model.parameters())[0,0,0] > 0: + model_name = "large-v1" + else: + model_name = "large-v2" + return _get_alignment_heads(model_name, num_layers, num_heads) + +def _get_alignment_heads(model_name, num_layers, num_heads): + dump = _ALIGNMENT_HEADS[model_name] + array = np.frombuffer(gzip.decompress(base64.b85decode(dump)), dtype=bool).copy() + mask = torch.from_numpy(array).reshape(num_layers, num_heads) + alignment_heads = mask.to_sparse() + return alignment_heads + +def _get_number_of_parameters(model): + num_parameters = 0 + for name, p in model.named_parameters(): + if name in ["decoder.proj_out.weight", "model.encoder.embed_positions.weight"]: + continue + num_parameters += p.numel() + return num_parameters + +from typing import Optional, Union +def load_model( + name: str, + device: Optional[Union[str, torch.device]] = None, + backend: str = DEFAULT_BACKEND, + download_root: str = None, + in_memory: bool = False, +): + """ + Load a model from the given name or path. + + Parameters + ---------- + name : str + Name of the model or path to the model. + Examples: + - OpenAI-Whisper identifier: "large-v3", "medium.en", ... + - HuggingFace identifier: "openai/whisper-large-v3", "distil-whisper/distil-large-v2", ... + - File name: "path/to/model.pt", "path/to/model.ckpt", "path/to/model.bin" + - Folder name: "path/to/folder". The folder must contain either "pytorch_model.bin", "model.safetensors", or sharded versions of those, or "whisper.ckpt". + device : str or torch.device, optional + Device to use. If None, use CUDA if there is a GPU available, otherwise CPU. + backend : str, optional + Backend to use. Either "transformers" or "openai-whisper". + download_root : str, optional + Root folder to download the model to. If None, use the default download root (typically: ~/.cache) + in_memory : bool, optional + Whether to preload the model weights into host memory. + """ + if backend == "transformers": + try: + import transformers + except ImportError: + raise ImportError(f"If you want to use transformers backend, please install first the transformers library") + if name in whisper.available_models(): + name = f"openai/whisper-{name}" + # TODO: use download_root + # TODO: does in_memory makes sense? + cache_dir=os.path.join(download_root, "huggingface", "hub") if download_root else None, + try: + generation_config = transformers.GenerationConfig.from_pretrained(name, cache_dir=cache_dir) + except OSError: + generation_config = transformers.GenerationConfig.from_pretrained("openai/whisper-tiny", cache_dir=cache_dir) + processor = transformers.WhisperProcessor.from_pretrained(name, cache_dir=cache_dir) + if device is None: + device = "cuda" if torch.cuda.is_available() else "cpu" + precision = torch.float32 + model = transformers.WhisperForConditionalGeneration.from_pretrained( + name, + # load_in_8bit=True, + # load_in_4bit=True, + torch_dtype=precision, + # torch_dtype=torch.bfloat16, + # attn_implementation="flash_attention_2", + # attn_implementation="sdpa", + cache_dir=cache_dir, + ) + # model = model.to_bettertransformer() + + model = model.to(device) + return TransformerWhisperAsOpenAIWhisper(model, processor, generation_config, precision) + + elif backend not in ["openai", "openai-whisper"]: + raise ValueError(f"Got unexpected backend {backend}") + + extension = os.path.splitext(name)[-1] if os.path.isfile(name) else None + + if name in whisper.available_models() or extension == ".pt": + return whisper.load_model( + name, + device=device, + download_root=os.path.join(download_root, "whisper") if download_root else None, + in_memory=in_memory + ) + + # Otherwise, assume transformers + if extension in [".ckpt", ".bin"]: + model_path = name + else: + # Search for the cached file (download if necessary) + try: + import transformers + except ImportError: + raise ImportError(f"If you are trying to download a HuggingFace model with {name}, please install first the transformers library") + from transformers.utils import cached_file + + kwargs = dict( + cache_dir=os.path.join(download_root, "huggingface", "hub") if download_root else None, + use_auth_token=None, + revision=None, + ) + try: + model_path = cached_file(name, "pytorch_model.bin", **kwargs) + except OSError as err: + try: + model_path = None + for candidate in ["whisper.ckpt", "pytorch_model.bin.index.json", "model.safetensors", "model.safetensors.index.json"]: + try: + model_path = cached_file(name, candidate, **kwargs) + except OSError: + continue + if candidate.endswith("index.json"): + index_file = model_path + mapping = json.load(open(index_file)) + assert "weight_map" in mapping + assert isinstance(mapping["weight_map"], dict) + model_path = list(set(mapping["weight_map"].values())) + folder = os.path.dirname(index_file) + model_path = [os.path.join(folder, p) for p in model_path] + break + assert model_path is not None + except: + raise RuntimeError(f"Original error: {err}\nCould not find model {name} from HuggingFace nor local folders.") + # Load HF Model + hf_state_dict = torch_load(model_path) + + # Rename layers + for key in list(hf_state_dict.keys())[:]: + new_key = hf_to_whisper_states(key) + if new_key is None: + hf_state_dict.pop(key) + elif new_key != key: + hf_state_dict[new_key] = hf_state_dict.pop(key) + + + # Init Whisper Model and replace model weights + dims = whisper.model.ModelDimensions(**states_to_dim(hf_state_dict)) + + if "proj_out.weight" in hf_state_dict: + hf_state_dict["decoder.proj_out.weight"] = hf_state_dict.pop("proj_out.weight") + logger.warning("Using untied projection layer") + whisper_model = WhisperUntied(dims) + else: + whisper_model = whisper.model.Whisper(dims) + + whisper_model.load_state_dict(hf_state_dict) + del hf_state_dict + if hasattr(whisper_model, "alignment_heads"): + del whisper_model.alignment_heads # Will be recomputed later + whisper_model = whisper_model.to(device) + return whisper_model + +def torch_load(model_path): + if isinstance(model_path, list): + hf_state_dict = {} + for p in model_path: + d = torch_load(p) + for k in d: + assert k not in hf_state_dict, f"Found duplicate key {k} in {p}" + hf_state_dict.update(d) + else: + assert isinstance(model_path, str) + if model_path.endswith(".safetensors"): + from safetensors import safe_open + hf_state_dict = {} + with safe_open(model_path, framework="pt", device="cpu") as f: + for k in f.keys(): + hf_state_dict[k] = f.get_tensor(k) + else: + hf_state_dict = torch.load(model_path, map_location="cpu") + return hf_state_dict + +# Some helpers to manage transformers/openai-whisper model + +class TransformerWhisperAsOpenAIWhisper: + """ + Wrapper to use a transformers model as a whisper model (at least in whisper-timestamped) + """ + + def __init__(self, model, processor, generation_config, precision): + + self.model = model # transformers.WhisperForConditionalGeneration + self.processor = processor # transformers.WhisperProcessor + self.generation_config = generation_config # transformers.GenerationConfig + + self.device = model.device + self.precision = precision + + # Dimensions + model_config = model.config + self.dims = whisper.model.ModelDimensions( + n_mels = model_config.num_mel_bins, # model.get_encoder().get_input_embeddings().in_channels, # 80 + n_audio_ctx = model_config.max_source_positions, # 1500 + n_audio_state = model_config.d_model, # model.get_encoder().get_input_embeddings().out_channels, # 768 + n_audio_head = model_config.encoder_attention_heads, # model.get_encoder().layers[0].self_attn.num_heads, + n_audio_layer = model_config.encoder_layers, # len(model.get_encoder().layers), + n_vocab = model_config.vocab_size, # model.get_decoder().get_input_embeddings().num_embeddings, # ~51865 + n_text_ctx = model_config.max_length, # 448 + n_text_state = model_config.d_model, # model.get_decoder().get_input_embeddings().embedding_dim, # 768 + n_text_head = model_config.decoder_attention_heads, # model.get_decoder().layers[0].self_attn.num_heads, + n_text_layer = model_config.decoder_layers, # len(model.get_decoder().layers), + ) + + # Tokenization + self.tokenizer = processor.tokenizer + ( + self.tokenizer.sot, + self.tokenizer.eot, + self.tokenizer.timestamp_begin, + self.tokenizer.no_speech, + self.tokenizer.no_timestamps, + ) = self.tokenizer.convert_tokens_to_ids([ + "<|startoftranscript|>", + "<|endoftext|>", + "<|0.00|>", + "<|nospeech|>", + "<|notimestamps|>", + ]) + if self.tokenizer.decode([self.tokenizer.timestamp_begin], decode_with_timestamps=True) != "<|0.00|>": + # Sometimes, the tokenizer is weird and it is impossible to get the timestamp_begin token easily (e.g. with "qanastek/whisper-tiny-french-cased") + logger.warning("Getting timestamp_begin token is not straightforward for this model") + i = self.tokenizer.no_timestamps + 1 + maxi = i + 1000 + while self.tokenizer.decode([i], decode_with_timestamps=True) != "<|0.00|>": + i += 1 + if i == maxi: + raise RuntimeError("Could not find timestamp_begin token") + self.tokenizer.timestamp_begin = i + + self.tokenizer.all_language_tokens = self.tokenizer.convert_tokens_to_ids([ + t for t in self.tokenizer.additional_special_tokens if len(t) in [6,7] + ]) + # Update old Whisper generation config (ex: error: "The generation config is outdated and is thus not compatible with the `task` argument to `generate` [...] update the generation config as per the instructions https://github.com/huggingface/transformers/issues/25084#issuecomment-1664398224") + if not hasattr(self.generation_config, "lang_to_id"): + self.generation_config.lang_to_id = dict( + (self.tokenizer.decode(itoken), itoken) + for itoken in self.tokenizer.all_language_tokens + ) + if not hasattr(self.generation_config, "task_to_id"): + self.generation_config.task_to_id = dict( + (task, self.tokenizer.encode("<|" + task + "|>", add_special_tokens=False)[0]) + for task in ["transcribe", "translate"]) + self.tokenizer.to_language_token = lambda language: self.generation_config.lang_to_id["<|" + norm_language(language) + "|>"] + self.tokenizer.to_task_token = lambda task: self.generation_config.task_to_id[task] + + self.tokenizer.to_timestamp_token = lambda t: self.tokenizer.encode(f"<|{t:0.2f}|>", add_special_tokens=False)[0] + self.tokenizer.decode_with_timestamps = lambda tokens: self.tokenizer.decode(tokens, decode_with_timestamps=True) + + self.generation_config.no_timestamps_token_id = self.tokenizer.no_timestamps + self.model.generation_config = self.generation_config + + # Access to layers (renamed attributes) + self.decoder = self.model.get_decoder() + self.decoder.ln = self.decoder.layer_norm + self.decoder.token_embedding = self.decoder.embed_tokens + self.decoder.blocks = self.decoder.layers + for block in self.decoder.blocks: + block.cross_attn = block.encoder_attn + + # From the config + if hasattr(generation_config, "is_multilingual"): + self.is_multilingual = generation_config.is_multilingual + else: + self.is_multilingual = generation_config.is_multilingual = (self.tokenizer.sot != 50257) + + # Alignment heads + if hasattr(generation_config, "alignment_heads"): + a = generation_config.alignment_heads + self.alignment_heads = torch.sparse_coo_tensor(np.array(a).transpose(), [True]*len(a)).coalesce().to(self.device) + + def named_parameters(self): + return self.model.named_parameters() + + def transcribe(self, audio, use_token_timestamps=False, **kwargs): + + # Decoding options + # TODO: double check that this setup is correct + generation_config = self.generation_config + generation_config.num_beams = kwargs.get("beam_size", None) or 1 + temperature = kwargs.get("temperature", 0.0) + if isinstance(temperature, (list, tuple)): + # Not supported with transformers + temperature = min(temperature) + if temperature != 0.0: + generation_config.do_sample = True + generation_config.temperature = temperature + generation_config.top_k = kwargs.get("best_of", None) + + initial_prompt = kwargs.get("initial_prompt") + prompt_ids = self.processor.get_prompt_ids(initial_prompt) if (initial_prompt and initial_prompt.strip()) else None + + generate_kwargs = dict( + return_dict_in_generate = True, + return_segments = True, + return_timestamps = True, + return_token_timestamps = use_token_timestamps, + max_length = self.dims.n_text_ctx, + is_multilingual = self.is_multilingual, + prompt_ids = prompt_ids, + generation_config = generation_config, + ) + if self.is_multilingual: + generate_kwargs["language"] = generate_kwargs.get("language") + generate_kwargs["task"] = generate_kwargs.get("task", "transcribe") + + # Extract features + features = self.processor( + audio, + return_tensors="pt", + sampling_rate=16_000, + truncation=False, + ).input_features.to(self.device) + + # Transcribe + output = self.model.generate( + features.to(self.precision), + **generate_kwargs + ) + + # Because the output format is different when there is only one segment (e.g. audio duration < 30 seconds)... (WTF) + if "segments" not in output: + tokens = output.sequences[0] + new_output = { + "segments": [[{ + "tokens": tokens[1:], + "start": torch.tensor(0.0), + "result": { + "sequences": output.sequences[0], + "past_key_values": output.past_key_values, + } + }]] + } + if use_token_timestamps: + new_output["segments"][0][0]["result"]["token_timestamps"] = output.token_timestamps[0] + output = new_output + + # Language detection + first_segment_tokens = output["segments"][0][0]["tokens"].tolist() + if self.tokenizer.sot in first_segment_tokens: + i_sot = first_segment_tokens.index(self.tokenizer.sot) + else: + i_sot = -1 + if self.is_multilingual: + language = self.tokenizer.decode([first_segment_tokens[i_sot+1]], decode_with_timestamps=True) + assert len(language) in [6,7], f"Unexpected language detected: '{language}' ({first_segment_tokens[i_sot+1]}) in '{self.tokenizer.decode(first_segment_tokens, decode_with_timestamps=True)}'" + language = language[2:-2] + else: + language = "en" + + if use_token_timestamps: + remove_punctuation_from_words = kwargs.get("remove_punctuation_from_words", False) + use_space = should_use_space(language) + + full_text = "" + segments = [] + for id, (segment_dict, segment) in enumerate(self._iter_segments(output, prompt_ids)): + + segment_dict = segment_dict | { + "temperature": temperature, + # "avg_logprob": -0.6982866287231445, + # "compression_ratio": 0.5294117647058824, + # "no_speech_prob": 0.019023602828383446 + } + + # Accumulate + if use_token_timestamps: + tokens = segment_dict["tokens_no_timestamp"] + offset = segment_dict["offset"] + all_tokens = segment["result"]["sequences"].tolist() + token_timestamps = segment["result"]["token_timestamps"] + assert len(all_tokens) == len(token_timestamps) + n_tokens = len(tokens) + for i in range(0, len(all_tokens) + 1 - n_tokens): + if all_tokens[i:i+n_tokens] == tokens: + token_timestamps = token_timestamps[i:i+n_tokens+1] + break + assert len(tokens)+1 == len(token_timestamps) + split_tokens = split_tokens_on_spaces if use_space else split_tokens_on_unicode + words, word_tokens, word_tokens_indices = split_tokens(tokens, self.tokenizer, remove_punctuation_from_words=remove_punctuation_from_words) + words_dicts = [] + i_end = 0 + for w, toks in zip(words, word_tokens_indices): + i_start = i_end + i_end = i_start + len(toks) + words_dicts.append({ + "text": w, + "start": offset + token_timestamps[i_start].item(), + "end": offset + token_timestamps[i_end].item(), + # "probability": 0.199 + }) + segment_dict["words"] = words_dicts + + segment_dict.pop("tokens_no_timestamp") + segment_dict.pop("offset") + segments.append(segment_dict) + full_text += segment_dict["text"] + + output_dict = { + "text": full_text, + "segments": segments, + } + if not kwargs.get("language"): + output_dict["language"] = language + + return output_dict + + def _iter_segments(self, output, prompt_ids): + + id = -1 + for sub_segments in output["segments"]: + for segment in sub_segments: + id += 1 + chunk_start = round(max(0, segment["start"].item()), 2) + tokens = segment["tokens"] + if id == 0 and prompt_ids is not None: + tokens = tokens[len(prompt_ids):] + time_tokens = [(i, t.item()) for i, t in enumerate(tokens) if t >= self.tokenizer.timestamp_begin] + i = 0 + while i < len(time_tokens): + i_start, token_start = time_tokens[i] + relative_start = round((token_start - self.tokenizer.timestamp_begin) * AUDIO_TIME_PER_TOKEN, 2) + assert relative_start >= 0 + if i == 0: + offset = chunk_start - relative_start + assert offset >= 0, f"Got negative offset ({offset}) with {chunk_start=} and {relative_start=}" + has_end = i + 1 < len(time_tokens) + if has_end: + i_end, token_end = time_tokens[i+1] + # Ends on either consecutive timestamps, or the next timestamp followed by <|endoftext|> + while i + 2 < len(time_tokens): + if time_tokens[i+2][0] == i_end + 1: break + if i_end + 1 >= len(tokens) or tokens[i_end+1] in [self.tokenizer.eot]: break + logger.warning(f"Unexpected prediction without 2 consecutive timestamps") + i += 1 + i_end, token_end = time_tokens[i+1] + relative_end = round((token_end - self.tokenizer.timestamp_begin) * AUDIO_TIME_PER_TOKEN, 2) + else: + i_end = len(tokens) - 1 + if tokens[i_end] == self.tokenizer.eot: i_end -= 1 + relative_end = SEGMENT_DURATION + start = offset + relative_start + duration = relative_end - relative_start + assert duration >= 0, f"Got negative duration ({duration}) with {relative_end=} and {relative_start=}" + tokens_with_timestamps = tokens[i_start:i_end+1] # include timestamps + text = self.tokenizer.decode(tokens_with_timestamps, skip_special_tokens=True) + tokens_with_timestamps = tokens_with_timestamps.tolist() + tokens_no_timestamp = tokens_with_timestamps[1:-1] if has_end else tokens_with_timestamps[1:] + i += 2 + if not len(tokens_no_timestamp): continue + yield ( + { + "id": id, + "seek": round(offset * SAMPLE_RATE / HOP_LENGTH), + "start": start, + "end": start + duration, + "text": text, + "tokens": tokens_with_timestamps, + "tokens_no_timestamp": tokens_no_timestamp, + "offset": offset, + }, + segment, + ) + + + def __call__(self, mfcc, tokens): + output = self.model(mfcc.to(self.precision), decoder_input_ids=tokens, output_attentions=True) + return output.logits + + +def is_transformer_model(model): + return isinstance(model, TransformerWhisperAsOpenAIWhisper) + + +# Credit: https://github.com/openai/whisper/discussions/830 +def hf_to_whisper_states(text): + # From Speechbrain + if text == "_mel_filters": + return None + + # From PEFT + if "default" in text: + # print(f"WARNING: Ignoring {text}") + return None + if text.startswith("base_model.model."): + text = text[len("base_model.model."):] + + text = re.sub('.layers.', '.blocks.', text) + text = re.sub('.self_attn.', '.attn.', text) + text = re.sub('.q_proj.', '.query.', text) + text = re.sub('.k_proj.', '.key.', text) + text = re.sub('.v_proj.', '.value.', text) + text = re.sub('.out_proj.', '.out.', text) + text = re.sub('.fc1.', '.mlp.0.', text) + text = re.sub('.fc2.', '.mlp.2.', text) + text = re.sub('.fc3.', '.mlp.3.', text) + text = re.sub('.fc3.', '.mlp.3.', text) + text = re.sub('.encoder_attn.', '.cross_attn.', text) + text = re.sub('.cross_attn.ln.', '.cross_attn_ln.', text) + text = re.sub('.embed_positions.weight', '.positional_embedding', text) + text = re.sub('.embed_tokens.', '.token_embedding.', text) + text = re.sub('model.', '', text) + text = re.sub('attn.layer_norm.', 'attn_ln.', text) + text = re.sub('.final_layer_norm.', '.mlp_ln.', text) + text = re.sub('encoder.layer_norm.', 'encoder.ln_post.', text) + text = re.sub('decoder.layer_norm.', 'decoder.ln.', text) + return text + +def states_to_dim(state_dict): + n_audio_state = len(state_dict['encoder.ln_post.bias']) + n_text_state = len(state_dict["decoder.ln.bias"]) + return { + "n_mels": state_dict["encoder.conv1.weight"].shape[1], # 80 + "n_vocab": state_dict["decoder.token_embedding.weight"].shape[0], # 51864 / 51865 + "n_audio_ctx": state_dict["encoder.positional_embedding"].shape[0], # 1500 + "n_audio_state": n_audio_state, # 384 / 512 / 768 / 1024 / 1280 + "n_audio_head": n_audio_state // 64, # 6 / 8 / 12 / 16 / 20 + "n_audio_layer": len(set([".".join(k.split(".")[:3]) for k in state_dict.keys() if "encoder.blocks." in k])), # 4 / 6 / 12 / 24 / 32 + "n_text_ctx": state_dict["decoder.positional_embedding"].shape[0], # 448 + "n_text_state": n_text_state, # 384 / 512 / 768 / 1024 / 1280 + "n_text_head": n_text_state // 64, # 6 / 8 / 12 / 16 / 20 + "n_text_layer": len(set([".".join(k.split(".")[:3]) for k in state_dict.keys() if "decoder.blocks." in k])), # 4 / 6 / 12 / 24 / 32 + } + +class TextDecoderUntied(whisper.model.TextDecoder): + """ + Same as TextDecoder but with untied weights + """ + def __init__(self, *args, **kwargs): + import torch + super().__init__(*args, **kwargs) + + n_vocab, n_state = self.token_embedding.weight.shape + + self.proj_out = torch.nn.Linear(n_state, n_vocab, bias=False) + + def forward(self, x, xa, kv_cache = None): + offset = next(iter(kv_cache.values())).shape[1] if kv_cache else 0 + x = self.token_embedding(x) + self.positional_embedding[offset : offset + x.shape[-1]] + x = x.to(xa.dtype) + + for block in self.blocks: + x = block(x, xa, mask=self.mask, kv_cache=kv_cache) + + x = self.ln(x) + + # logits = self.proj_out(x).float() + # logits = (x @ torch.transpose(self.proj_out.weight.to(x.dtype), 0, 1)).float() + logits = self.proj_out.to(x.dtype)(x).float() + + return logits + +class WhisperUntied(whisper.model.Whisper): + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self.decoder = TextDecoderUntied( + self.dims.n_vocab, + self.dims.n_text_ctx, + self.dims.n_text_state, + self.dims.n_text_head, + self.dims.n_text_layer, + ) + +def cli(): + + import os + import sys + import argparse + import json + + from whisper.utils import str2bool, optional_float, optional_int + + try: + # Old whisper version # Before https://github.com/openai/whisper/commit/da600abd2b296a5450770b872c3765d0a5a5c769 + from whisper.utils import write_txt, write_srt, write_vtt + write_tsv = lambda transcript, file: write_csv(transcript, file, sep="\t", header=True, text_first=False, format_timestamps=lambda x: round(1000 * x)) + + except ImportError: + # New whisper version + from whisper.utils import get_writer + + def do_write(transcript, file, output_format): + writer = get_writer(output_format, os.path.curdir) + try: + return writer.write_result({"segments": list(transcript)}, file, { + "highlight_words": False, + "max_line_width": None, + "max_line_count": None, + }) + except TypeError: + # Version <= 20230314 + return writer.write_result({"segments": transcript}, file) + def get_do_write(output_format): + return lambda transcript, file: do_write(transcript, file, output_format) + + write_txt = get_do_write("txt") + write_srt = get_do_write("srt") + write_vtt = get_do_write("vtt") + write_tsv = get_do_write("tsv") + + parser = argparse.ArgumentParser( + description='Transcribe a single audio with whisper and compute word timestamps', + formatter_class=argparse.ArgumentDefaultsHelpFormatter + ) + parser.add_argument('-v', '--version', help="show version and exit", action='version', version=f'{__version__}') + parser.add_argument('--versions', help="show versions (of whisper-timestamped and whisper) and exit", action='version', + version=f'{__version__} -- Whisper {whisper.__version__} in {os.path.realpath(os.path.dirname(whisper.__file__))}') + + parser.add_argument('audio', help="audio file(s) to transcribe", nargs='+') + parser.add_argument('--model', help=f"name of the Whisper model to use. Examples: {', '.join(whisper.available_models())}", default="small") + parser.add_argument("--model_dir", default=None, help="the path to save model files; uses ~/.cache/whisper by default", type=str) + parser.add_argument("--device", default=get_default_device(), help="device to use for PyTorch inference") + parser.add_argument("--backend", default=DEFAULT_BACKEND, help="Which backend to use", choices=["openai-whisper", "transformers"], type=str) + parser.add_argument("--output_dir", "-o", default=None, help="directory to save the outputs", type=str) + valid_formats = ["txt", "vtt", "srt", "tsv", "csv", "json"] + def str2output_formats(string): + if string == "all": + return valid_formats + formats = string.split(",") + for format in formats: + if format not in valid_formats: + raise ValueError(f"Expected one of {valid_formats}, got {format}") + return formats + parser.add_argument("--output_format", "-f", default="all", help=f"Format(s) of the output file(s). Possible formats are: {', '.join(valid_formats)}. Several formats can be specified by using commas (ex: \"json,vtt,srt\"). By default (\"all\"), all available formats will be produced", type=str2output_formats) + + parser.add_argument("--task", default="transcribe", help="whether to perform X->X speech recognition ('transcribe') or X->English translation ('translate')", choices=["transcribe", "translate"], type=str) + parser.add_argument('--language', help=f"language spoken in the audio, specify None to perform language detection.", choices=sorted(whisper.tokenizer.LANGUAGES.keys()) + sorted([k.title() for k in whisper.tokenizer.TO_LANGUAGE_CODE.keys()]), default=None) + # f"{', '.join(sorted(k+'('+v+')' for k,v in whisper.tokenizer.LANGUAGES.items()))} + + parser.add_argument('--vad', default=False, help="whether to run Voice Activity Detection (VAD) to remove non-speech segment before applying Whisper model (removes hallucinations). " + "Can be: True, False, auditok, silero (default when vad=True), silero:3.1 (or another version), or a list of timestamps in seconds (e.g. \"[(0.0, 3.50), (32.43, 36.43)]\"). " + "Note: Some additional libraries might be needed (torchaudio and onnxruntime for silero, auditok for auditok)." + ) + parser.add_argument('--detect_disfluencies', default=False, help="whether to try to detect disfluencies, marking them as special words [*]", type=str2bool) + parser.add_argument('--recompute_all_timestamps', default=not TRUST_WHISPER_TIMESTAMP_BY_DEFAULT, help="Do not rely at all on Whisper timestamps (Experimental option: did not bring any improvement, but could be useful in cases where Whipser segment timestamp are wrong by more than 0.5 seconds)", type=str2bool) + parser.add_argument("--punctuations_with_words", default=True, help="whether to include punctuations in the words", type=str2bool) + + parser.add_argument("--temperature", default=0.0, help="temperature to use for sampling", type=float) + parser.add_argument("--best_of", type=optional_int, default=None if USE_EFFICIENT_BY_DEFAULT else 5, help="number of candidates when sampling with non-zero temperature") + parser.add_argument("--beam_size", type=optional_int, default=None if USE_EFFICIENT_BY_DEFAULT else 5, help="number of beams in beam search, only applicable when temperature is zero") + parser.add_argument("--patience", type=float, default=None, help="optional patience value to use in beam decoding, as in https://arxiv.org/abs/2204.05424, the default (1.0) is equivalent to conventional beam search") + parser.add_argument("--length_penalty", type=float, default=None, help="optional token length penalty coefficient (alpha) as in https://arxiv.org/abs/1609.08144, uses simple length normalization by default") + + parser.add_argument("--suppress_tokens", default="-1", help="comma-separated list of token ids to suppress during sampling; '-1' will suppress most special characters except common punctuations", type=str) + parser.add_argument("--initial_prompt", default=None, help="optional text to provide as a prompt for the first window.", type=str) + parser.add_argument("--condition_on_previous_text", default=True, help="if True, provide the previous output of the model as a prompt for the next window; disabling may make the text inconsistent across windows, but the model becomes less prone to getting stuck in a failure loop", type=str2bool) + parser.add_argument("--fp16", default=None, help="whether to perform inference in fp16; Automatic by default (True if GPU available, False otherwise)", type=str2bool) + + parser.add_argument("--temperature_increment_on_fallback", default=0.0 if USE_EFFICIENT_BY_DEFAULT else 0.2, help="temperature to increase when falling back when the decoding fails to meet either of the thresholds below", type=optional_float) + parser.add_argument("--compression_ratio_threshold", default=2.4, help="if the gzip compression ratio is higher than this value, treat the decoding as failed", type=optional_float) + parser.add_argument("--logprob_threshold", default=-1.0, help="if the average log probability is lower than this value, treat the decoding as failed", type=optional_float) + parser.add_argument("--no_speech_threshold", default=0.6, help="if the probability of the <|nospeech|> token is higher than this value AND the decoding has failed due to `logprob_threshold`, consider the segment as silence", type=optional_float) + parser.add_argument("--threads", default=0, help="number of threads used by torch for CPU inference; supercedes MKL_NUM_THREADS/OMP_NUM_THREADS", type=optional_int) + + parser.add_argument("--compute_confidence", default=True, help="whether to compute confidence scores for words", type=str2bool) + parser.add_argument("--verbose", type=str2bool, default=False, help="whether to print out the progress and debug messages of Whisper") + parser.add_argument('--plot', help="plot word alignments (save the figures if an --output_dir is specified, otherwhise just show figures that have to be closed to continue)", default=False, action="store_true") + parser.add_argument('--debug', help="print some debug information about word alignment", default=False, action="store_true") + + class ActionSetAccurate(argparse.Action): + def __init__(self, option_strings, dest, nargs=None, **kwargs): + assert nargs is None + super().__init__(option_strings, dest, nargs=0, **kwargs) + def __call__(self, parser, namespace, values, option_string=None): + setattr(namespace, "best_of", 5) + setattr(namespace, "beam_size", 5) + setattr(namespace, "temperature_increment_on_fallback", 0.2) + parser.add_argument('--accurate', help="Shortcut to use the same default option as in openai-whisper (best_of=5, beam_search=5, temperature_increment_on_fallback=0.2)", action=ActionSetAccurate) + + class ActionSetEfficient(argparse.Action): + def __init__(self, option_strings, dest, nargs=None, **kwargs): + assert nargs is None + super().__init__(option_strings, dest, nargs=0, **kwargs) + def __call__(self, parser, namespace, values, option_string=None): + setattr(namespace, "best_of", None) + setattr(namespace, "beam_size", None) + setattr(namespace, "temperature_increment_on_fallback", None) + parser.add_argument('--efficient', help="Shortcut to disable beam size and options that requires to sample several times, for an efficient decoding", action=ActionSetEfficient) + + parser.add_argument('--naive', help="use naive approach, doing inference twice (once to get the transcription, once to get word timestamps and confidence scores).", default=False, action="store_true") + + args = parser.parse_args().__dict__ + args.pop("accurate") + args.pop("efficient") + + temperature = args.pop("temperature") + temperature_increment_on_fallback = args.pop("temperature_increment_on_fallback") + if temperature_increment_on_fallback: + temperature = tuple(np.arange(temperature, 1.0 + 1e-6, temperature_increment_on_fallback)) + else: + temperature = [temperature] + + threads = args.pop("threads") + if threads: + torch.set_num_threads(threads) + + audio_files = args.pop("audio") + + model = args.pop("model") + device = args.pop("device") + model_dir = args.pop("model_dir") + + if device.lower().startswith("cuda"): + force_cudnn_initialization(device) + + output_format = args.pop("output_format") + backend = args.pop("backend") + + model = load_model(model, device=device, download_root=model_dir, backend=backend) + + plot_word_alignment = args.pop("plot") + + debug = args.pop("debug") + logging.basicConfig() + if debug: + logger.setLevel(logging.DEBUG) + # This supposes to plug a logger with name "WHISPER" into Whisper source code (no harm if it's not set) + logging.getLogger("WHISPER").setLevel(logging.DEBUG) + + output_dir = args.pop("output_dir") + if output_dir and not os.path.isdir(output_dir): + os.makedirs(output_dir) + + args["naive_approach"] = args.pop("naive") + args["remove_punctuation_from_words"] = not args.pop("punctuations_with_words") + args["compute_word_confidence"] = args.pop("compute_confidence") + args["trust_whisper_timestamps"] = not args.pop("recompute_all_timestamps") + + for audio_path in audio_files: + + outname = os.path.join(output_dir, os.path.basename(audio_path)) if output_dir else None + + result = transcribe_timestamped( + model, audio_path, + temperature=temperature, + plot_word_alignment=outname if (outname and plot_word_alignment) else plot_word_alignment, + **args + ) + + if output_dir: + + if "json" in output_format: + # save JSON + with open(outname + ".words.json", "w", encoding="utf-8") as js: + json.dump(result, js, indent=2, ensure_ascii=False) + + # save TXT + if "txt" in output_format: + with open(outname + ".txt", "w", encoding="utf-8") as txt: + write_txt(result["segments"], file=txt) + + # save VTT + if "vtt" in output_format: + with open(outname + ".vtt", "w", encoding="utf-8") as vtt: + write_vtt(remove_keys(result["segments"], "words"), file=vtt) + with open(outname + ".words.vtt", "w", encoding="utf-8") as vtt: + write_vtt(flatten(result["segments"], "words"), file=vtt) + + # save SRT + if "srt" in output_format: + with open(outname + ".srt", "w", encoding="utf-8") as srt: + write_srt(remove_keys(result["segments"], "words"), file=srt) + with open(outname + ".words.srt", "w", encoding="utf-8") as srt: + write_srt(flatten(result["segments"], "words"), file=srt) + + # save CSV + if "csv" in output_format: + with open(outname + ".csv", "w", encoding="utf-8") as csv: + write_csv(result["segments"], file=csv) + with open(outname + ".words.csv", "w", encoding="utf-8") as csv: + write_csv(flatten(result["segments"], "words"), file=csv) + + # save TSV + if "tsv" in output_format: + with open(outname + ".tsv", "w", encoding="utf-8") as csv: + write_tsv(result["segments"], file=csv) + with open(outname + ".words.tsv", "w", encoding="utf-8") as csv: + write_tsv(flatten(result["segments"], "words"), file=csv) + + elif not args["verbose"]: + + json.dump(filtered_keys(result), sys.stdout, indent=2, ensure_ascii=False) + + +def filtered_keys(result, keys = [ + "text", + "segments", "words", + "language", + "start", + "end", + "confidence", + "language_probs", + "speech_activity", +]): + if isinstance(result, dict): + return {k: (filtered_keys(v, keys) if k not in ["language_probs"] else v) for k, v in result.items() if k in keys} + if isinstance(result, list): + return [filtered_keys(v, keys) for v in result] + if isinstance(result, float): + return round(result, 2) + return result + + +if __name__ == "__main__": + cli()