Language is inherent and compulsory for human communication. Whether expressed written, spoken or signed, language ensures understanding between people of the same and different regions.
African languages (over 2000) are complex and truly low-resourced. These languages receive minimal attention: the datasets required for NLP applications are difficult to discover and existing research is hard to reproduce.
However this is changing. With the growing awareness and effort to include more low-resourced languages in NLP research, African languages have recently been a major subject of research in natural language processing.
The presentation is the story of the dynamic duo, Chris and Bonaventure, as they work towards tackling the NLP challenges facing African languages. The talk will cover a range of topics with a focus on the OkwuGbé end-to-end speech recognition system for Fon and Igbo
Bonaventure Dossou is a research Intern at Mila Quebec AI Institute, working under the supervision of Professor Yoshua Bengio. His research areas include Machine & Deep learning (and its application in computer vision, natural language processing for Healthcare and African Languages), Computational biology, Network Science Approaches in Biology and Medicine.
Chris Emezue is a master student at the Technical University of Munich. He works with SIEMENS and also recently joined the Mila Institute as a research intern. His research areas include machine/deep learning, reinforcement learning, multilingualism, knowledge-graph representations, speech processing, and AfricaNLP.