karim155/WolBanking77

Intent classification models have made a lot of progress in recent years. However, previous studies primarily focus on high-resource languages datasets, which results in a gap for low-resource languages and for regions with a high rate of illiterate people where languages are more spoken than read or written. This is the case in Senegal, for example, where Wolof is spoken by around 90% of the population, with an illiteracy rate of 42% for the country. Wolof is actually spoken by more than 10 million people in West African region.

To tackle such limitations, we release a Wolof Banking Speech Intent Classification Dataset (WolBanking77), for academic research in intent classification. WolBanking77 currently contains 9,791 text sentences in the banking domain and more than 4 hours of spoken sentences.

This dataset is suitable for :

• Customer Intent Detection
• Machine Translation in French & Wolof
• Automatic Speech Recognition in Wolof
• Comparing different machine learning models for Intent Classification

Dataset Content:

• text dir - Contains text dataset
• audio dir - Contains audio dataset
• train.csv – Text Training dataset (includes label target)
• test.csv – Text Test dataset (no label target)
• train.parquet - Audio Training dataset
• test.parquet - Audio Test dataset
• questions.csv - Customer queries
• responses.csv - Bot responses

Target Variable:

• label→ The client intent

Features:

• input – Client’s query in English (text)
• input_fr – Client’s query in French (text)
• input_wo – Client’s query in Wolof (text)
• label – Client's Intent (categorical)

License

CC BY 4.0 – Open for public use.

Inspiration

• Can you predict the client intent?
• How well do different machine learning models perform on this classification task?

Citation

To cite this work, please use the following reference:

@inproceedings{
    kandji2025wolbanking,
    title={WolBanking77: Wolof Banking Speech Intent Classification Dataset},
    author={Abdou Karim KANDJI and Frederic Precioso and Cheikh BA and Samba NDIAYE and Augustin NDIONE},
    booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
    year={2025},
    url={https://openreview.net/forum?id=7k0JBDeHAv}
}

@misc{
    kandji2025wolbanking77wolofbankingspeech,
    title={WolBanking77: Wolof Banking Speech Intent Classification Dataset}, 
    author={Abdou Karim Kandji and Frédéric Precioso and Cheikh Ba and Samba Ndiaye and Augustin Ndione},
    year={2025},
    eprint={2509.19271},
    archivePrefix={arXiv},
    primaryClass={cs.CL},
    url={https://arxiv.org/abs/2509.19271}, 
}