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Kallaama: A Transcribed Speech Dataset about Agriculture in the Three Most Widely Spoken Languages in Senegal

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arxiv 2404.01991 v1 pith:FLAAJPCO submitted 2024-04-02 cs.CL

classification cs.CL
keywords languageslanguagespeechtechnologieswolofagriculturedatasetkallaama
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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  1. Voice of a Continent: Mapping Africa's Speech Technology Frontier

    cs.CL 2025-05 conditional novelty 6.0 of 10

    A new benchmark and fine-tuned Simba models improve speech recognition, synthesis, and language identification across 61 African languages, but the claimed state of the art lacks comparisons to prior task-specific systems.

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