Natural language processing model for African languages

Researchers have developed an AI model to help computers work more efficiently with a wider variety of languages. African languages have received relatively little attention from computer scientists, so few natural language processing capabilities have been available to large swaths of the continent. A new language model, developed by researchers at the University of Waterloo's David R. Cheriton School of Computer Science, begins to fill that gap by enabling computers to analyze text in African languages for many useful tasks. The new neural network model, which the researchers have dubbed AfriBERTa, uses deep-learning techniques to achieve state-of-the-art results for low-resource languages. The neural network language model works specifically with 11 African languages, such as Amharic, Hausa, and Swahili, spoken collectively by more than 400 million people.