|
--- |
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license: cc-by-4.0 |
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dataset_info: |
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- config_name: assamese |
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features: |
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dtype: audio |
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- config_name: bengali |
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- config_name: dogri |
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dtype: string |
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splits: |
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num_bytes: 3603495138.825 |
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num_examples: 23721 |
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download_size: 3568871899 |
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dataset_size: 3603495138.825 |
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- config_name: gujarati |
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features: |
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dtype: audio |
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dtype: string |
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num_bytes: 16321596906.35 |
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num_examples: 137965 |
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download_size: 17665902401 |
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- config_name: hindi |
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features: |
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dtype: audio |
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num_examples: 734675 |
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- config_name: kannada |
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num_examples: 192208 |
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- config_name: maithili |
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num_examples: 22233 |
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download_size: 2895972814 |
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- config_name: malayalam |
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features: |
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dtype: audio |
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num_bytes: 17608171088.553 |
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num_examples: 224323 |
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download_size: 19431260422 |
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- config_name: marathi |
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features: |
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dtype: audio |
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- name: text |
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dtype: string |
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num_bytes: 42353055748.775 |
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num_examples: 336475 |
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download_size: 38603401934 |
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dataset_size: 42353055748.775 |
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- config_name: nepali |
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features: |
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dtype: audio |
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dtype: string |
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splits: |
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num_bytes: 5214995797.048 |
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num_examples: 31997 |
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download_size: 4990235585 |
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dataset_size: 5214995797.048 |
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- config_name: odia |
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features: |
|
- name: audio_filepath |
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dtype: audio |
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- name: text |
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dtype: string |
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- name: duration |
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dtype: float64 |
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dtype: string |
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splits: |
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num_bytes: 12687640571.75 |
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num_examples: 126675 |
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download_size: 16473690962 |
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dataset_size: 12687640571.75 |
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- config_name: punjabi |
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features: |
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- name: audio_filepath |
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dtype: audio |
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- name: text |
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dtype: string |
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- name: duration |
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dtype: float64 |
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- name: lang |
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dtype: string |
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splits: |
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num_bytes: 3054398341.146 |
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num_examples: 21118 |
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download_size: 3181612927 |
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dataset_size: 3054398341.146 |
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- config_name: sanskrit |
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features: |
|
- name: audio_filepath |
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dtype: audio |
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- name: text |
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dtype: string |
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- name: duration |
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dtype: float64 |
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dtype: string |
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splits: |
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num_bytes: 2036760741.337 |
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num_examples: 14177 |
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dataset_size: 2036760741.337 |
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- config_name: tamil |
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features: |
|
- name: audio_filepath |
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dtype: audio |
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- name: text |
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dtype: string |
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dtype: float64 |
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dtype: string |
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splits: |
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num_examples: 281508 |
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dataset_size: 33855148157.352 |
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- config_name: telugu |
|
features: |
|
- name: audio_filepath |
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dtype: audio |
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- name: text |
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dtype: string |
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- name: duration |
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dtype: float64 |
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dtype: string |
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splits: |
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num_bytes: 5722466966.018 |
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num_examples: 56082 |
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download_size: 5886818756 |
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dataset_size: 5722466966.018 |
|
configs: |
|
- config_name: assamese |
|
data_files: |
|
- split: train |
|
path: assamese/train-* |
|
- config_name: bengali |
|
data_files: |
|
- split: train |
|
path: bengali/train-* |
|
- config_name: dogri |
|
data_files: |
|
- split: train |
|
path: dogri/train-* |
|
- config_name: gujarati |
|
data_files: |
|
- split: train |
|
path: gujarati/train-* |
|
- config_name: hindi |
|
data_files: |
|
- split: train |
|
path: hindi/train-* |
|
- config_name: kannada |
|
data_files: |
|
- split: train |
|
path: kannada/train-* |
|
- config_name: konkani |
|
data_files: |
|
- split: train |
|
path: konkani/train-* |
|
- config_name: maithili |
|
data_files: |
|
- split: train |
|
path: maithili/train-* |
|
- config_name: malayalam |
|
data_files: |
|
- split: train |
|
path: malayalam/train-* |
|
- config_name: marathi |
|
data_files: |
|
- split: train |
|
path: marathi/train-* |
|
- config_name: nepali |
|
data_files: |
|
- split: train |
|
path: nepali/train-* |
|
- config_name: odia |
|
data_files: |
|
- split: train |
|
path: odia/train-* |
|
- config_name: punjabi |
|
data_files: |
|
- split: train |
|
path: punjabi/train-* |
|
- config_name: sanskrit |
|
data_files: |
|
- split: train |
|
path: sanskrit/train-* |
|
- config_name: tamil |
|
data_files: |
|
- split: train |
|
path: tamil/train-* |
|
- config_name: telugu |
|
data_files: |
|
- split: train |
|
path: telugu/train-* |
|
--- |
|
|
|
# Shrutilipi |
|
|
|
<div style="display: flex; gap: 5px;"> |
|
<a href="https://github.com/AI4Bharat/Lahaja"><img src="https://img.shields.io/badge/GITHUB-black?style=flat&logo=github&logoColor=white" alt="GitHub"></a> |
|
<a href="https://arxiv.org/abs/2408.11440"><img src="https://img.shields.io/badge/arXiv-2411.02538-red?style=flat" alt="ArXiv"></a> |
|
<a href="https://creativecommons.org/licenses/by/4.0/"><img src="https://img.shields.io/badge/License-CC%20BY%204.0-lightgrey.svg" alt="CC BY 4.0"></a> |
|
</div> |
|
|
|
## Dataset Description |
|
|
|
- **Homepage:** [Shrutilipi](https://huggingface.co/datasets/ai4bharat/Shrutilipi) |
|
- **Repository:** [Github](https://github.com/AI4Bharat/shrutilipi) |
|
- **Paper:** [Effectiveness of Mining Audio and Text Pairs from Public Data for Improving ASR Systems for Low-Resource Languages](https://arxiv.org/abs/2208.12666) |
|
|
|
## Overview |
|
|
|
Shrutilipi is a labelled ASR corpus obtained by mining parallel audio and text pairs at the document scale from All India Radio news bulletins for 12 Indian languages: Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Odia, Punjabi, Sanskrit, Tamil, Telugu, Urdu. The corpus has over 6400 hours of data across all languages. |
|
|
|
This work is funded by Bhashini, MeitY and Nilekani Philanthropies |
|
|
|
## Usage |
|
|
|
The [datasets](https://huggingface.co/docs/datasets) library enables you to load and preprocess the dataset directly in Python. Ensure you have an active HuggingFace access token (obtainable from [Hugging Face settings](https://huggingface.co/settings/tokens)) before proceeding. |
|
|
|
To load the dataset, run: |
|
|
|
```python |
|
from datasets import load_dataset |
|
# Load the dataset from the HuggingFace Hub |
|
dataset = load_dataset("ai4bharat/Shrutilipi","bengali",split="train") |
|
# Check the dataset structure |
|
print(dataset) |
|
``` |
|
|
|
You can also stream the dataset by enabling the `streaming=True` flag: |
|
|
|
```python |
|
from datasets import load_dataset |
|
dataset = load_dataset("ai4bharat/Shrutilipi","bengali",split="train", streaming=True) |
|
print(next(iter(dataset))) |
|
``` |
|
|
|
## Citation |
|
|
|
If you use Shrutilipi in your work, please cite us: |
|
|
|
```bibtex |
|
@inproceedings{DBLP:conf/icassp/BhogaleRJDKKK23, |
|
author = {Kaushal Santosh Bhogale and |
|
Abhigyan Raman and |
|
Tahir Javed and |
|
Sumanth Doddapaneni and |
|
Anoop Kunchukuttan and |
|
Pratyush Kumar and |
|
Mitesh M. Khapra}, |
|
title = {Effectiveness of Mining Audio and Text Pairs from Public Data for |
|
Improving {ASR} Systems for Low-Resource Languages}, |
|
booktitle = {{ICASSP}}, |
|
pages = {1--5}, |
|
publisher = {{IEEE}}, |
|
year = {2023} |
|
} |
|
``` |
|
|
|
## License |
|
|
|
This dataset is released under the [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). |
|
|
|
## Contact |
|
|
|
For any questions or feedback, please contact: |
|
- Kaushal Bhogale (kaushal98b@gmail.com) |
|
|
|
|
