Kallaama: A Transcribed Speech Dataset about Agriculture in the Three Most Widely Spoken Languages in Senegal
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Abstract (arXiv)
This work is part of the Kallaama project, whose objective is to produce and disseminate national languages corpora for speech technologies developments, in the field of agriculture. Except for Wolof, which benefits from some language data for natural language processing, national languages of Senegal are largely ignored by language technology providers. However, such technologies are keys to the protection, promotion and teaching of these languages. Kallaama focuses on the 3 main spoken languages by Senegalese people: Wolof, Pulaar and Sereer. These languages are widely spoken by the population, with around 10 million of native Senegalese speakers, not to mention those outside the country. However, they remain under-resourced in terms of machine-readable data that can be used for automatic processing and language technologies, all the more so in the agricultural sector. We release a transcribed speech dataset containing 125 hours of recordings, about agriculture, in each of the above-mentioned languages. These resources are specifically designed for Automatic Speech Recognition purpose, including traditional approaches. To build such technologies, we provide textual corpora in Wolof and Pulaar, and a pronunciation lexicon containing 49,132 entries from the Wolof dataset.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 4 of its 22 references that are in the map. First posted on arXiv 2 Apr 2024.
Builds on
4 of 22 references.
References · 4
- 2020The State and Fate of Linguistic Diversity and Inclusion in the NLP Worldcited by 798
- 2022FLEURS: Few-shot Learning Evaluation of Universal Representations of Speechcited by 469
- 2022Towards Afrocentric NLP for African Languages: Where We Are and Where We Can Gocited by 47
- 2022Square One Bias in NLP: Towards a Multi-Dimensional Exploration of the Research Manifoldcited by 29
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Citing papers per year: 2024: 1; 2025: 4; 2026: 2.
7 papers.
- 2024AfriHuBERT: A self-supervised speech representation model for African languagescited by 18
- 2025Charting the Landscape of African NLP: Mapping Progress and Shaping the Road Aheadcited by 16
- 2025Voice of a Continent: Mapping Africa's Speech Technology Frontiercited by 4
- 2025Speech Language Models for Under-Represented Languages: Insights from Wolofcited by 2
- 2025WolBanking77: Wolof Banking Speech Intent Classification Datasetcited by 0
- 2026Cross-lingual Matryoshka Representation Learning across Speech and Textcited by 0
- 2026Improving Language Identification for Code-Switched Utterances with Integer Linear Programmingcited by 0
- 2026Improving Language Identification for Code-Switched Utterances with Integer Linear Programming4 Sep 2026
- 2026Cross-lingual Matryoshka Representation Learning across Speech and Text23 Feb 2026
- 2025WolBanking77: Wolof Banking Speech Intent Classification Dataset23 Sep 2025
- 2025Speech Language Models for Under-Represented Languages: Insights from Wolof18 Sep 2025
- 2025Charting the Landscape of African NLP: Mapping Progress and Shaping the Road Ahead27 May 2025
- 2025Voice of a Continent: Mapping Africa's Speech Technology Frontier24 May 2025
- 2024AfriHuBERT: A self-supervised speech representation model for African languages30 Sep 2024