5 accepted papers
Data curation for under-resource languages enables the development of more accurate and culturally sensitive natural language processing models. However, the scarcity of well-structured multilingual datasets remains a challenge for advancing machine translation in these languages, especially for Afr…
Illiteracy is a predictor of many negative social and personal outcomes. Illiteracy rates are particularly high in countries with underresourced languages, where few books exist that are suitable for children to learn to read from. We present GAIfE (Generative AI for Education), a toolchain and work…
In this paper, we present AfricaPOS, the largest part-of-speech (POS) dataset for 20 typologically diverse African languages. We discuss the challenges in annotating POS for these languages using the universal dependencies (UD) guidelines. We conducted extensive POS baseline experiments using both c…
Recent advances in the pre-training for language models leverage large-scale datasets to create multilingual models. However, low-resource languages are mostly left out in these datasets. This is primarily because many widely spoken languages that are not well represented on the web and therefore ex…
African languages are spoken by over a billion people, but they are under-represented in NLP research and development. Multiple challenges exist, including the limited availability of annotated training and evaluation datasets as well as the lack of understanding of which settings, languages, and re…