Clement Odoje

Department of Linguistics and African Languages

University of Ibadan


Solomon O. Akinola

Computer Engineering,

College of Engineering,

Afe Babalola University,

P.M.B. 5454,

Ado Ekiti 


The challenges of Machine Translation (MT) and in particular Statistical Machine Translation (SMT) have been explored and categorized. But little is known about African languages which are said to be resource scare languages. Hence, this paper explored the challenges of SMT for African languages using English-Yoruba MT as case study. Fagunwa's books and its English translated equivalent versions were used as corpus and Moses was used as the language toolkit. While the challenges were inexhaustible it was found that the challenges of Africa SMT can be categorized into two: technical and sociocultural determinants.