|
--- |
|
dataset_info: |
|
features: |
|
- name: audio |
|
dtype: audio |
|
- name: transcript |
|
dtype: string |
|
- name: english |
|
dtype: string |
|
splits: |
|
- name: train |
|
num_bytes: 10917088956.322 |
|
num_examples: 39238 |
|
download_size: 10866820110 |
|
dataset_size: 10917088956.322 |
|
task_categories: |
|
- automatic-speech-recognition |
|
language: |
|
- pa |
|
tags: |
|
- punjabi |
|
- asr |
|
- transcription |
|
- translation |
|
pretty_name: Punjabi ASR |
|
size_categories: |
|
- 10K<n<100K |
|
--- |
|
|
|
# Dataset for Punjabi ASR |
|
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. |
|
|
|
``` |
|
@misc{https://doi.org/10.48550/arxiv.2208.12666, |
|
doi = {10.48550/ARXIV.2208.12666}, |
|
url = {https://arxiv.org/abs/2208.12666}, |
|
author = {Bhogale, Kaushal Santosh and Raman, Abhigyan and Javed, Tahir and Doddapaneni, Sumanth and Kunchukuttan, Anoop and Kumar, Pratyush and Khapra, Mitesh M.}, |
|
title = {Effectiveness of Mining Audio and Text Pairs from Public Data for Improving ASR Systems for Low-Resource Languages}, |
|
publisher = {arXiv}, |
|
year = {2022}, |
|
copyright = {arXiv.org perpetual, non-exclusive license} |
|
} |
|
``` |
