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metadata
license: cc-by-4.0
language:
  - as
  - bn
  - gu
  - hi
  - kn
  - ml
  - mr
  - ne
  - or
  - pa
  - ta
  - te
  - sd
  - ur
  - en
pretty_name: Vanipedia
extra_gated_fields:
  Name: text
  Email: text
  Affiliation: text
  Position: text
size_categories:
  - 10K<n<100K
multilinguality:
  - multilingual
dataset_info:
  - config_name: en2indic
    features:
      - name: chunked_audio_filepath
        dtype: audio
      - name: start_time
        dtype: float64
      - name: end_time
        dtype: float64
      - name: duration
        dtype: float64
      - name: video_id
        dtype: string
      - name: hi_translation
        dtype: string
      - name: gu_translation
        dtype: string
      - name: mr_translation
        dtype: string
      - name: ta_translation
        dtype: string
      - name: kn_translation
        dtype: string
      - name: te_translation
        dtype: string
      - name: ml_translation
        dtype: string
      - name: pa_translation
        dtype: string
      - name: or_translation
        dtype: string
      - name: bn_translation
        dtype: string
      - name: as_translation
        dtype: string
      - name: sd_translation
        dtype: string
      - name: ur_translation
        dtype: string
      - name: ne_translation
        dtype: string
    splits:
      - name: en2indic
        num_bytes: 63805046224.289
        num_examples: 52541
    download_size: 52456892557
    dataset_size: 63805046224.289
configs:
  - config_name: en2indic
    data_files:
      - split: en2indic
        path: En-Indic/train-*

BhasaAnuvaad: A Speech Translation Dataset for 13 Indian Languages

GitHub ArXiv CC BY 4.0

Dataset Description

Overview

BhasaAnuvaad, is the largest Indic-language AST dataset spanning over 44,400 hours of speech and 17M text segments for 13 of 22 scheduled Indian languages and English.

This repository consists of parallel data for Speech Translation from Vanipedia, a subset of BhasaAnuvaad.

How to use

The datasets library allows you to load and pre-process your dataset in pure Python, at scale. The dataset can be downloaded and prepared in one call to your local drive by using the load_dataset function.

  • Before downloading first follow the following steps:

    1. Gain access to the dataset and get the HF access token from: https://huggingface.co/settings/tokens.
    2. Install dependencies and login HF:
      • Install Python
      • Run pip install librosa soundfile datasets huggingface_hub[cli]
      • Login by huggingface-cli login and paste the HF access token. Check here for details.

For example, to download the (indic2en or en2indic) config, simply specify the corresponding config name (i.e., "indic2en" for Hindi):

from datasets import load_dataset
bhasaanuvaad = load_dataset("ai4bharat/Vanipedia", "en2indic", split="en2indic")

Using the datasets library, you can also stream the dataset on-the-fly by adding a streaming=True argument to the load_dataset function call. Loading a dataset in streaming mode loads individual samples of the dataset at a time, rather than downloading the entire dataset to disk.

from datasets import load_dataset
bhasaanuvaad = load_dataset("ai4bharat/Vanipedia", "en2indic", split="en2indic", streaming=True)
print(next(iter(bhasaanuvaad)))

Citation

If you use BhasaAnuvaad in your work, please cite us:

@article{jain2024bhasaanuvaad,
  title   = {BhasaAnuvaad: A Speech Translation Dataset for 14 Indian Languages},
  author  = {Sparsh Jain and Ashwin Sankar and Devilal Choudhary and Dhairya Suman and Nikhil Narasimhan and Mohammed Safi Ur Rahman Khan and Anoop Kunchukuttan and Mitesh M Khapra and Raj Dabre},
  year    = {2024},
  journal = {arXiv preprint arXiv: 2411.04699}
}

License

This dataset is released under the CC BY 4.0.

Contact

For any questions or feedback, please contact:

Please contact us for any copyright concerns.

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