The Ghanaian NLP Landscape: A First Look
It addresses the underrepresentation of African languages in AI, focusing on Ghanaian languages to support linguistic diversity and cultural heritage.
This study conducted a comprehensive survey of NLP research on Ghanaian languages, identifying methodologies, datasets, and techniques, and created a roadmap to improve accessibility for researchers.
Despite comprising one-third of global languages, African languages are critically underrepresented in Artificial Intelligence (AI), threatening linguistic diversity and cultural heritage. Ghanaian languages, in particular, face an alarming decline, with documented extinction and several at risk. This study pioneers a comprehensive survey of Natural Language Processing (NLP) research focused on Ghanaian languages, identifying methodologies, datasets, and techniques employed. Additionally, we create a detailed roadmap outlining challenges, best practices, and future directions, aiming to improve accessibility for researchers. This work serves as a foundational resource for Ghanaian NLP research and underscores the critical need for integrating global linguistic diversity into AI development.