arXiv:2604.08448v2 Announce Type: replace Abstract: AfriVoices-KE is a large-scale multilingual speech dataset comprising approximately 3,000 hours of audio across five Kenyan languages: Dholuo, Kikuyu, Kalenjin, Maasai, and Somali. The dataset includes 750 hours of scripted speech and 2,250 hours of spontaneous speech, collected from 4,777 native speakers across diverse regions and demographics. This work addresses the critical underrepresentation of African languages in speech technology by providing a high-quality, linguistically diverse resource. Data collection followed a dual methodology
The increasing availability of large language models and the push for AI localization are driving a global effort to build robust, diverse datasets for underserved languages.
This dataset directly addresses the critical underrepresentation of African languages in AI, enabling the development of more inclusive and effective speech technologies for a significant portion of the global population.
The creation of this high-quality, multilingual speech dataset for Kenyan languages lowers the barrier for AI development in these linguistic contexts, potentially leading to diverse applications previously hindered by data scarcity.
- · Kenyan language speakers
- · African AI developers
- · Speech technology companies
- · Academic researchers in NLP
- · Developers solely focused on English/major languages
- · AI models with inherent biases against African languages
Increased development and deployment of speech-enabled AI applications tailored for Kenyan languages.
Enhanced digital inclusion and economic opportunities for speakers of these languages through better access to AI services.
The establishment of a precedent and methodology for similar data collection efforts, accelerating AI development across other underserved African languages and potentially fostering regional AI hubs.
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