Automatic Speech Recognition for the Basaà Language: A Low-Resource Approach
Sophie Gertrude Ngo Mock, Charles Moudina Varmantchaonala, Paul Dayang, Jean Michel Nlong, Christopher Gies
Abstract
The rapid advancement of Artificial Intelligence (AI) and Natural Language Processing (NLP) has revolutionized the way humans interact with machines. Among the most impactful developments is Automatic Speech Recognition (ASR), which enables computers to convert spoken language into text. Systems such as those built on deep neural networks, transformer architectures, and self-supervised learning have achieved near-human performance for well-resourced languages such as English and French. Yet, these advances have disproportionately benefited a small fraction of the world's languages.