A Functional NLP System for Twi (Akan) Using Limited Data

David Sasu, Dennis Asamoah Owusu

Research output: Journal Article or Conference Article in JournalConference articleResearchpeer-review


Natural Language Processing (NLP) continues to advance. How- ever, native Ghanaian languages like many other languages in the world remain untouched. Limited availability of annotated data in these languages is, perhaps, the primary limiting factor. This work explores the development of a useful and practical NLP system for Twi, a native Ghanaian language, under the constraint of limited data. The result is a system developed using only 4.65 minutes of annotated speech data that allows searching for selected Twi songs by saying the song title in Twi.
Original languageEnglish
JournalACM SIGCAS Conference on Computing and Sustainable Societies
Number of pages2
Publication statusPublished - 2019


  • Natural Language Processing
  • Machine Learning


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