license: cc-by-4.0
language:
- as
- bn
- gu
- hi
- kn
- ml
- mr
- ta
- te
- en
pretty_name: NPTEL
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: text
dtype: string
- name: pred_text
dtype: string
- name: course_id
dtype: string
- name: video_id
dtype: string
- name: audio_filepath
dtype: string
- name: start_time
dtype: float64
- name: duration
dtype: float64
- name: alignment_score
dtype: float64
- name: hi_text
dtype: string
- name: hi_mining_score
dtype: float64
- name: gu_text
dtype: string
- name: gu_mining_score
dtype: float64
- name: mr_text
dtype: string
- name: mr_mining_score
dtype: float64
- name: ta_text
dtype: string
- name: ta_mining_score
dtype: float64
- name: kn_text
dtype: string
- name: kn_mining_score
dtype: float64
- name: te_text
dtype: string
- name: te_mining_score
dtype: float64
- name: ml_text
dtype: string
- name: ml_mining_score
dtype: float64
- name: pa_text
dtype: string
- name: pa_mining_score
dtype: float64
- name: or_text
dtype: string
- name: or_mining_score
dtype: float64
- name: bn_text
dtype: string
- name: bn_mining_score
dtype: float64
- name: as_text
dtype: string
- name: as_mining_score
dtype: float64
splits:
- name: en2indic
num_bytes: 55526811299.416
num_examples: 1586872
download_size: 45959084544
dataset_size: 55526811299.416
- config_name: indic2en
features:
- name: chunked_audio_filepath
dtype: audio
- name: text
dtype: string
- name: pred_text
dtype: string
- name: course_id
dtype: string
- name: video_id
dtype: string
- name: audio_filepath
dtype: string
- name: start_time
dtype: float64
- name: duration
dtype: float64
- name: alignment_score
dtype: float64
- name: en_text
dtype: string
- name: en_mining_score
dtype: float64
splits:
- name: assamese
num_bytes: 5641197
num_examples: 5731
- name: bengali
num_bytes: 153911157
num_examples: 149086
- name: gujarati
num_bytes: 307555467
num_examples: 300880
- name: hindi
num_bytes: 615054195
num_examples: 521028
- name: kannada
num_bytes: 249177676
num_examples: 219331
- name: malayalam
num_bytes: 350945469
num_examples: 320242
- name: marathi
num_bytes: 294217612
num_examples: 289652
- name: tamil
num_bytes: 583254616
num_examples: 538750
- name: telugu
num_bytes: 340136633
num_examples: 302087
download_size: 4706779931
dataset_size: 2899894022
configs:
- config_name: en2indic
data_files:
- split: en2indic
path: En-Indic/train-*
- 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: 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 NPTEL, 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 loginand 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/NPTEL", "indic2en", split="hindi")
or
from datasets import load_dataset
bhasaanuvaad = load_dataset("ai4bharat/NPTEL", "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/NPTEL", "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.