metadata

license: cc-by-4.0
language:
  - hi
  - kn
  - ta
  - te
  - ur
pretty_name: SeamlessAlign
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: audio_filepath
        dtype: audio
      - name: text_lid_score
        dtype: string
      - name: laser_score
        dtype: string
      - name: text
        dtype: string
      - name: duration
        dtype: float64
      - name: transcription
        dtype: string
      - name: sonar_score
        dtype: float64
    splits:
      - name: hindi
        num_bytes: 601710273
        num_examples: 1021145
      - name: kannada
        num_bytes: 38444950
        num_examples: 68563
      - name: tamil
        num_bytes: 348770246
        num_examples: 478542
      - name: telugu
        num_bytes: 216133931
        num_examples: 329449
      - name: urdu
        num_bytes: 600628399
        num_examples: 1107620
    download_size: 2154999646
    dataset_size: 1805687799
configs:
  - config_name: indic2en
    data_files:
      - split: hindi
        path: Indic-En/hin/train-*
      - split: kannada
        path: Indic-En/kan/train-*
      - split: tamil
        path: Indic-En/tam/train-*
      - split: telugu
        path: Indic-En/tel/train-*
      - split: urdu
        path: Indic-En/urd/train-*

BhasaAnuvaad: A Speech Translation Dataset for 13 Indian Languages

Dataset Description

Homepage: Bhasaanuvaad Collection
Repository: Github
Paper: BhasaAnuvaad: A Speech Translation Dataset for 13 Indian Languages

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 SeamlessAlign, 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/SeamlessAlign", "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/SeamlessAlign", "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:

Raj Dabre ([email protected])
Sparsh Jain ([email protected])
Ashwin Sankar ([email protected])
Nikhil Narasimhan ([email protected])
Mohammed Safi Ur Rahman Khan ([email protected])

Datasets:

ai4bharat
/

SeamlessAlign