Computational modelling of personal pronouns for English to Yorùbà machine translation system

Abstract

Translating third person singular pronouns from English to Yoruba is yet to receive research attention. The issue can be understood if the translation is speech to speech. In the literature, the authors translate sentence without considering the gender of the author or doer as it is in the English (source language) sentence. This does pose a problem to the reader of English to Yoruba translated sentences. We envisaged that there is need to represent she/he/it differently unlike the way we are translating it now. Presently, she/he/it are translated as O. We proposed ways of representing the three third person singular pronouns; binrin, kunrin and unkan. Feminine (She) is binrin, masculine (he) is kunrin and non-human (it) is unkan. We developed English to Yoruba machine translation (IFEMT1) system that can translate simple English sentence text to Yoruba sentence text using the existing and proposed third person singular pronouns translation processes. We used rule based approach and python programming language to implement the IFEMT1 system. The system graphical user interface (GUI) can display the English sentences (to be translated), translated Yoruba sentences for the existing and our proposed translations.