  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.
