A Survey of Text and Speech Resources for Hausa and Fongbe: Availability, Quality, and Gaps for NLP Development
A new survey paper details the current landscape of natural language processing (NLP) resources for Hausa and Fongbe, two West African languages. The research systematically catalogs available text and speech datasets, pre-trained models, and benchmarks, finding that Hausa has more diverse text resources while Fongbe has seen recent academic focus on speech data. The paper identifies critical gaps, such as domain-specific text for Fongbe and dedicated speech corpora for Hausa, offering recommendations for future NLP development in these languages. AI
IMPACT Identifies critical resource gaps for developing NLP tools for Hausa and Fongbe, potentially guiding future research and development efforts.