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
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 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:
- Gain access to the dataset and get the HF access token from: https://huggingface.co/settings/tokens.
- 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:
- Raj Dabre ([email protected])
- Sparsh Jain ([email protected])
- Ashwin Sankar ([email protected])
- Nikhil Narasimhan ([email protected])
- Mohammed Safi Ur Rahman Khan ([email protected])
Please contact us for any copyright concerns.