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--- |
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annotations_creators: |
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- expert-generated |
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language_creators: |
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- found |
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language: |
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- en |
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license: |
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- unlicense |
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multilinguality: |
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- monolingual |
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size_categories: |
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- 10K<n<100K |
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source_datasets: |
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- original |
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task_categories: |
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- automatic-speech-recognition |
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- text-to-speech |
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- text-to-audio |
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task_ids: [] |
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paperswithcode_id: ljspeech |
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pretty_name: LJ Speech |
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dataset_info: |
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config_name: main |
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features: |
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- name: id |
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dtype: string |
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- name: audio |
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dtype: |
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audio: |
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sampling_rate: 22050 |
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- name: file |
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dtype: string |
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- name: text |
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dtype: string |
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- name: normalized_text |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 3860187268.0 |
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num_examples: 13100 |
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download_size: 3786217548 |
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dataset_size: 3860187268.0 |
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configs: |
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- config_name: main |
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data_files: |
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- split: train |
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path: main/train-* |
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default: true |
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train-eval-index: |
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- config: main |
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task: automatic-speech-recognition |
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task_id: speech_recognition |
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splits: |
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train_split: train |
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col_mapping: |
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file: path |
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text: text |
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metrics: |
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- type: wer |
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name: WER |
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- type: cer |
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name: CER |
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--- |
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|
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# Dataset Card for lj_speech |
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|
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## Table of Contents |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-fields) |
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- [Data Splits](#data-splits) |
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- [Dataset Creation](#dataset-creation) |
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- [Curation Rationale](#curation-rationale) |
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- [Source Data](#source-data) |
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- [Annotations](#annotations) |
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- [Personal and Sensitive Information](#personal-and-sensitive-information) |
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- [Considerations for Using the Data](#considerations-for-using-the-data) |
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- [Social Impact of Dataset](#social-impact-of-dataset) |
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- [Discussion of Biases](#discussion-of-biases) |
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- [Other Known Limitations](#other-known-limitations) |
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- [Additional Information](#additional-information) |
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- [Dataset Curators](#dataset-curators) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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- [Contributions](#contributions) |
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|
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## Dataset Description |
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|
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- **Homepage:** [The LJ Speech Dataset](https://keithito.com/LJ-Speech-Dataset/) |
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- **Repository:** [N/A] |
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- **Paper:** [N/A] |
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- **Leaderboard:** [Paperswithcode Leaderboard](https://paperswithcode.com/sota/text-to-speech-synthesis-on-ljspeech) |
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- **Point of Contact:** [Keith Ito](mailto:kito@kito.us) |
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|
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### Dataset Summary |
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|
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This is a public domain speech dataset consisting of 13,100 short audio clips of a single speaker reading passages from 7 non-fiction books in English. A transcription is provided for each clip. Clips vary in length from 1 to 10 seconds and have a total length of approximately 24 hours. |
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The texts were published between 1884 and 1964, and are in the public domain. The audio was recorded in 2016-17 by the LibriVox project and is also in the public domain. |
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|
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### Supported Tasks and Leaderboards |
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The dataset can be used to train a model for Automatic Speech Recognition (ASR) or Text-to-Speech (TTS). |
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- `automatic-speech-recognition`: An ASR model is presented with an audio file and asked to transcribe the audio file to written text. |
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The most common ASR evaluation metric is the word error rate (WER). |
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- `text-to-speech`, `text-to-audio`: A TTS model is given a written text in natural language and asked to generate a speech audio file. |
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A reasonable evaluation metric is the mean opinion score (MOS) of audio quality. |
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The dataset has an active leaderboard which can be found at https://paperswithcode.com/sota/text-to-speech-synthesis-on-ljspeech |
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### Languages |
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The transcriptions and audio are in English. |
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## Dataset Structure |
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### Data Instances |
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A data point comprises the path to the audio file, called `file` and its transcription, called `text`. |
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A normalized version of the text is also provided. |
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|
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``` |
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{ |
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'id': 'LJ002-0026', |
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'file': '/datasets/downloads/extracted/05bfe561f096e4c52667e3639af495226afe4e5d08763f2d76d069e7a453c543/LJSpeech-1.1/wavs/LJ002-0026.wav', |
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'audio': {'path': '/datasets/downloads/extracted/05bfe561f096e4c52667e3639af495226afe4e5d08763f2d76d069e7a453c543/LJSpeech-1.1/wavs/LJ002-0026.wav', |
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'array': array([-0.00048828, -0.00018311, -0.00137329, ..., 0.00079346, |
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0.00091553, 0.00085449], dtype=float32), |
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'sampling_rate': 22050}, |
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'text': 'in the three years between 1813 and 1816,' |
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'normalized_text': 'in the three years between eighteen thirteen and eighteen sixteen,', |
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} |
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``` |
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Each audio file is a single-channel 16-bit PCM WAV with a sample rate of 22050 Hz. |
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### Data Fields |
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- id: unique id of the data sample. |
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- file: a path to the downloaded audio file in .wav format. |
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- audio: A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: `dataset[0]["audio"]` the audio file is automatically decoded and resampled to `dataset.features["audio"].sampling_rate`. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the `"audio"` column, *i.e.* `dataset[0]["audio"]` should **always** be preferred over `dataset["audio"][0]`. |
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- text: the transcription of the audio file. |
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- normalized_text: the transcription with numbers, ordinals, and monetary units expanded into full words. |
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|
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### Data Splits |
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The dataset is not pre-split. Some statistics: |
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|
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- Total Clips: 13,100 |
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- Total Words: 225,715 |
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- Total Characters: 1,308,678 |
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- Total Duration: 23:55:17 |
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- Mean Clip Duration: 6.57 sec |
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- Min Clip Duration: 1.11 sec |
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- Max Clip Duration: 10.10 sec |
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- Mean Words per Clip: 17.23 |
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- Distinct Words: 13,821 |
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|
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## Dataset Creation |
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|
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### Curation Rationale |
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[Needs More Information] |
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### Source Data |
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#### Initial Data Collection and Normalization |
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This dataset consists of excerpts from the following works: |
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- Morris, William, et al. Arts and Crafts Essays. 1893. |
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- Griffiths, Arthur. The Chronicles of Newgate, Vol. 2. 1884. |
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- Roosevelt, Franklin D. The Fireside Chats of Franklin Delano Roosevelt. 1933-42. |
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- Harland, Marion. Marion Harland's Cookery for Beginners. 1893. |
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- Rolt-Wheeler, Francis. The Science - History of the Universe, Vol. 5: Biology. 1910. |
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- Banks, Edgar J. The Seven Wonders of the Ancient World. 1916. |
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- President's Commission on the Assassination of President Kennedy. Report of the President's Commission on the Assassination of President Kennedy. 1964. |
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|
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Some details about normalization: |
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- The normalized transcription has the numbers, ordinals, and monetary units expanded into full words (UTF-8) |
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- 19 of the transcriptions contain non-ASCII characters (for example, LJ016-0257 contains "raison d'être"). |
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- The following abbreviations appear in the text. They may be expanded as follows: |
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|
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| Abbreviation | Expansion | |
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|--------------|-----------| |
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| Mr. | Mister | |
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| Mrs. | Misess (*) | |
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| Dr. | Doctor | |
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| No. | Number | |
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| St. | Saint | |
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| Co. | Company | |
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| Jr. | Junior | |
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| Maj. | Major | |
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| Gen. | General | |
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| Drs. | Doctors | |
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| Rev. | Reverend | |
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| Lt. | Lieutenant | |
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| Hon. | Honorable | |
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| Sgt. | Sergeant | |
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| Capt. | Captain | |
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| Esq. | Esquire | |
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| Ltd. | Limited | |
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| Col. | Colonel | |
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| Ft. | Fort | |
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(*) there's no standard expansion for "Mrs." |
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|
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#### Who are the source language producers? |
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|
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[Needs More Information] |
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|
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### Annotations |
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|
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#### Annotation process |
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|
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- The audio clips range in length from approximately 1 second to 10 seconds. They were segmented automatically based on silences in the recording. Clip boundaries generally align with sentence or clause boundaries, but not always. |
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- The text was matched to the audio manually, and a QA pass was done to ensure that the text accurately matched the words spoken in the audio. |
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#### Who are the annotators? |
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Recordings by Linda Johnson from LibriVox. Alignment and annotation by Keith Ito. |
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### Personal and Sensitive Information |
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|
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The dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in this dataset. |
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|
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## Considerations for Using the Data |
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|
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### Social Impact of Dataset |
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[Needs More Information] |
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### Discussion of Biases |
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[Needs More Information] |
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### Other Known Limitations |
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- The original LibriVox recordings were distributed as 128 kbps MP3 files. As a result, they may contain artifacts introduced by the MP3 encoding. |
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## Additional Information |
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### Dataset Curators |
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The dataset was initially created by Keith Ito and Linda Johnson. |
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### Licensing Information |
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Public Domain ([LibriVox](https://librivox.org/pages/public-domain/)) |
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### Citation Information |
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|
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``` |
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@misc{ljspeech17, |
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author = {Keith Ito and Linda Johnson}, |
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title = {The LJ Speech Dataset}, |
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howpublished = {\url{https://keithito.com/LJ-Speech-Dataset/}}, |
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year = 2017 |
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} |
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``` |
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### Contributions |
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|
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Thanks to [@anton-l](https://github.com/anton-l) for adding this dataset. |