SYSTEMIC FUNCTIONAL GRAMMAR-BASED AUTOMATIC YORÙBÁ GRAMMAR CHECKER

Grammar checkers are readily available for high resource languages like English and French, but few are available for African languages, particularly Yorùbá. As a result, a Yorùbá language automatic grammar checker was created. Yorùbá words were gathered and used to create a digital dataset of Yorùbá words. Textbooks were consulted to get information on Yorùbá grammar. This information was used to formulate a computational model. The computational model followed the principle of Systemic Functional Grammar (SFG). Python programming language version 3.5 was used for the system implementation. Three hundred (300) sentences were used to test the accuracy of the grammar checker. The grammar checker performed well with values of accuracy of 93.33%, 97.78%, and 96.67% for simple, compound and complex declarative sentences respectively. Yorùbá digital content can now be automatically proofread for grammatical errors using the grammar checker. Its inclusion in software applications could enhance Yorùbá text processing. The developed digital dataset Yorùbá of words can be applied to various aspects of human language processing.