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---
license: cc-by-4.0
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download_size: 23450931018
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features:
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dtype: audio
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configs:
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data_files:
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path: assamese/valid-*
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path: assamese/train-*
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data_files:
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path: bengali/valid-*
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path: bengali/train-*
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path: bodo/train-*
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data_files:
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data_files:
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data_files:
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data_files:
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path: marathi/valid-*
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path: marathi/train-*
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path: nepali/valid-*
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path: nepali/train-*
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data_files:
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path: odia/valid-*
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path: odia/train-*
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data_files:
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path: punjabi/valid-*
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path: punjabi/train-*
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data_files:
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path: sanskrit/valid-*
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path: sanskrit/train-*
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data_files:
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path: santali/valid-*
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path: santali/train-*
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data_files:
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path: sindhi/valid-*
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path: sindhi/train-*
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data_files:
- split: valid
path: tamil/valid-*
- split: train
path: tamil/train-*
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data_files:
- split: valid
path: telugu/valid-*
- split: train
path: telugu/train-*
- config_name: urdu
data_files:
- split: valid
path: urdu/valid-*
- split: train
path: urdu/train-*
---
# IndicVoices
<div style="display: flex; gap: 5px;">
<a href="https://ai4bharat.iitm.ac.in/datasets/indicvoices"><img src="https://img.shields.io/badge/Data-green?style=flat" alt="Data"></a>
<a href="https://arxiv.org/abs/2403.01926"><img src="https://img.shields.io/badge/Paper-blue?style=flat" alt="Paper"></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:** [IndicVoices](https://ai4bharat.iitm.ac.in/datasets/indicvoices)
- **Paper:** [IndicVoices: A Diverse Indian Speech Dataset](https://arxiv.org/abs/2403.01926)
## Overview
IndicVoices is a dataset of natural and spontaneous speech comprising **12,000 hours** of audio. It includes read (8%), extempore (76%), and conversational (15%) speech from **22 Indian languages**. With contributions from **22 languages**, **22563 speakers** and coverage of **208 Indian districts**, this dataset captures the cultural, linguistic, and demographic diversity of India. Out of the total 12,000 hours, 3200 hours have been transcribed (with a median of 122 hours per language). The dataset provides an open-source blueprint for large-scale data collection, including standardized protocols, centralized tools, engaging prompts, quality control mechanisms, transcription guidelines, and annotation tools. IndicVoices also serves as the foundation for IndicASR—the first Automatic Speech Recognition (ASR) model supporting all 22 languages in the Eighth Schedule of the Indian Constitution.
## How to Use
The [datasets](https://huggingface.co/docs/datasets) library allows you to load and preprocess IndicVoices directly in Python. Before you start, please ensure that you have an active Hugging Face access token. You can obtain your token from [https://huggingface.co/settings/tokens](https://huggingface.co/settings/tokens) and login via the Hugging Face CLI.
For example, to load the dataset, simply run:
```python
from datasets import load_dataset
indicvoices = load_dataset("ai4bharat/IndicVoices", split="train")
```
You can also stream the dataset on-the-fly by setting the `streaming=True` flag:
```python
from datasets import load_dataset
indicvoices = load_dataset("ai4bharat/IndicVoices", split="train", streaming=True)
print(next(iter(indicvoices)))
```
## IndicASR
IndicASR is a multilingual ASR model trained on IndicVoices, supporting all 22 Indian languages.
### Checkpoint
- **IndicASR:** [Download Checkpoint](https://indic-asr-public.objectstore.e2enetworks.net/indicvoices_artifacts/indicvoices-no-ssl-acl.nemo)
## Collection and Transcription Platforms
### Collection Platform: Kathbath
Kathbath is an open-source, crowdsourcing framework designed for large-scale audio data collection. It features an Android frontend to facilitate microtask completion on mobile devices and is built on top of [Karya](https://github.com/AI4Bharat/Karya).
### Transcription Platform: Shoonya
Shoonya is an open-source platform for scalable data annotation and labeling. It supports multiple data types (e.g., parallel datasets, OCR, ASR, TTS) and provides versatile tools for efficient transcription.
[GitHub Repository: Shoonya](https://github.com/AI4Bharat/Shoonya)
## Citation
If you use IndicVoices in your work, please cite the paper:
```bibtex
@article{jain2024indicvoices,
title = {IndicVoices: A Diverse Dataset for Indian Speech},
author = {Authors from AI4Bharat},
year = {2024},
journal = {arXiv preprint arXiv:2403.01926}
}
```
## License
This dataset is released under the [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) license.
## Contact
For any questions or feedback, please reach out to the AI4Bharat team through the respective GitHub repositories or the contact details provided on the [IndicVoices Homepage](https://ai4bharat.iitm.ac.in/datasets/indicvoices).
## Links
- [IndicVoices Homepage](https://ai4bharat.iitm.ac.in/datasets/indicvoices)
- [IndicVoices Paper](https://arxiv.org/abs/2403.01926)
- [Kathbath (Collection Platform) on GitHub](https://github.com/AI4Bharat/Karya)
- [Shoonya (Transcription Platform) on GitHub](https://github.com/AI4Bharat/Shoonya)