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metadata
license: cc-by-4.0
language:
  - as
  - bn
  - gu
  - hi
  - kn
  - ml
  - mr
  - ne
  - sa
  - or
  - pa
  - ta
  - te
pretty_name: Spoken-Tutorial
extra_gated_fields:
  Name: text
  Email: text
  Affiliation: text
  Position: text
size_categories:
  - 10K<n<100K
multilinguality:
  - multilingual
dataset_info:
  - config_name: indic2en
    features:
      - name: chunked_audio_filepath
        dtype: audio
      - name: text
        dtype: string
      - name: pred_text
        dtype: string
      - name: audio_filepath
        dtype: string
      - name: start_time
        dtype: float64
      - name: duration
        dtype: float64
      - name: alignment_score
        dtype: float64
      - name: video_id
        dtype: string
      - name: en_mining_score
        dtype: float64
      - name: en_text
        dtype: string
    splits:
      - name: assamese
        num_bytes: 343067051.822
        num_examples: 12274
      - name: bengali
        num_bytes: 499502972.554
        num_examples: 30197
      - name: gujarati
        num_bytes: 678996297.963
        num_examples: 34647
      - name: hindi
        num_bytes: 648813013.415
        num_examples: 36613
      - name: kannada
        num_bytes: 243536824.95
        num_examples: 15066
      - name: malayalam
        num_bytes: 229315194.4
        num_examples: 13700
      - name: marathi
        num_bytes: 674304759.6
        num_examples: 42211
      - name: nepali
        num_bytes: 661894761.432
        num_examples: 1088
      - name: odia
        num_bytes: 57624292.742
        num_examples: 3317
      - name: punjabi
        num_bytes: 157501608.72
        num_examples: 8864
      - name: sanskrit
        num_bytes: 163037453.8
        num_examples: 7800
      - name: tamil
        num_bytes: 836957381.624
        num_examples: 35702
      - name: telugu
        num_bytes: 126877236.203
        num_examples: 6257
    download_size: 4666468514
    dataset_size: 5923297849.225
configs:
  - config_name: indic2en
    data_files:
      - split: assamese
        path: Indic-En/asm/train-*
      - split: bengali
        path: Indic-En/ben/train-*
      - split: gujarati
        path: Indic-En/guj/train-*
      - split: hindi
        path: Indic-En/hin/train-*
      - split: kannada
        path: Indic-En/kan/train-*
      - split: malayalam
        path: Indic-En/mal/train-*
      - split: marathi
        path: Indic-En/mar/train-*
      - split: odia
        path: Indic-En/ory/train-*
      - split: punjabi
        path: Indic-En/pan/train-*
      - split: sanskrit
        path: Indic-En/san/train-*
      - split: nepali
        path: Indic-En/npi/train-*
      - split: tamil
        path: Indic-En/tam/train-*
      - split: telugu
        path: Indic-En/tel/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 Spoken-Tutorial youtube channel, 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/Spoken-Tutorial", "indic2en", split="hindi")

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/Spoken-Tutorial", "indic2en", split="hindi", 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.

Links