---
license: cc-by-4.0
language: 
- ceb
- ind
- jav
- khm
- lao
- zlm
- mya
- sun
- tha
- tgl
- vie
- war
pretty_name: Voxlingua
task_categories: 
- speech-language-identification
tags: 
- speech-language-identification
---

VoxLingua107 is a comprehensive speech dataset designed for training spoken language identification models.
It comprises short speech segments sourced from YouTube videos, labeled based on the language indicated in the video
title and description. The dataset covers 107 languages and contains a total of 6628 hours of speech data,
averaging 62 hours per language. However, the actual amount of data per language varies significantly.
Additionally, there is a separate development set consisting of 1609 speech segments from 33 languages,
validated by at least two volunteers to ensure the accuracy of language representation.


## Languages

ceb, ind, jav, khm, lao, zlm, mya, sun, tha, tgl, vie, war

## Supported Tasks

Speech Language Identification

## Dataset Usage
### Using `datasets` library
```
from datasets import load_dataset
dset = datasets.load_dataset("SEACrowd/voxlingua", trust_remote_code=True)
```
### Using `seacrowd` library
```import seacrowd as sc
# Load the dataset using the default config
dset = sc.load_dataset("voxlingua", schema="seacrowd")
# Check all available subsets (config names) of the dataset
print(sc.available_config_names("voxlingua"))
# Load the dataset using a specific config
dset = sc.load_dataset_by_config_name(config_name="<config_name>")
```

More details on how to load the `seacrowd` library can be found [here](https://github.com/SEACrowd/seacrowd-datahub?tab=readme-ov-file#how-to-use).


## Dataset Homepage

[https://bark.phon.ioc.ee/voxlingua107/](https://bark.phon.ioc.ee/voxlingua107/)

## Dataset Version

Source: 1.0.0. SEACrowd: 2024.06.20.

## Dataset License

Creative Commons Attribution 4.0 (cc-by-4.0)

## Citation

If you are using the **Voxlingua** dataloader in your work, please cite the following:
```
@inproceedings{valk2021slt,
  title={{VoxLingua107}: a Dataset for Spoken Language Recognition},
  author={J{"o}rgen Valk and Tanel Alum{"a}e},
  booktitle={Proc. IEEE SLT Workshop},
  year={2021},
}


@article{lovenia2024seacrowd,
    title={SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages}, 
    author={Holy Lovenia and Rahmad Mahendra and Salsabil Maulana Akbar and Lester James V. Miranda and Jennifer Santoso and Elyanah Aco and Akhdan Fadhilah and Jonibek Mansurov and Joseph Marvin Imperial and Onno P. Kampman and Joel Ruben Antony Moniz and Muhammad Ravi Shulthan Habibi and Frederikus Hudi and Railey Montalan and Ryan Ignatius and Joanito Agili Lopo and William Nixon and Börje F. Karlsson and James Jaya and Ryandito Diandaru and Yuze Gao and Patrick Amadeus and Bin Wang and Jan Christian Blaise Cruz and Chenxi Whitehouse and Ivan Halim Parmonangan and Maria Khelli and Wenyu Zhang and Lucky Susanto and Reynard Adha Ryanda and Sonny Lazuardi Hermawan and Dan John Velasco and Muhammad Dehan Al Kautsar and Willy Fitra Hendria and Yasmin Moslem and Noah Flynn and Muhammad Farid Adilazuarda and Haochen Li and Johanes Lee and R. Damanhuri and Shuo Sun and Muhammad Reza Qorib and Amirbek Djanibekov and Wei Qi Leong and Quyet V. Do and Niklas Muennighoff and Tanrada Pansuwan and Ilham Firdausi Putra and Yan Xu and Ngee Chia Tai and Ayu Purwarianti and Sebastian Ruder and William Tjhi and Peerat Limkonchotiwat and Alham Fikri Aji and Sedrick Keh and Genta Indra Winata and Ruochen Zhang and Fajri Koto and Zheng-Xin Yong and Samuel Cahyawijaya},
    year={2024},
    eprint={2406.10118},
    journal={arXiv preprint arXiv: 2406.10118}
}

```