DESIGN AND IMPLEMENTATION OF ENGLISH TO YORUBA LANGUAGE TRANSLATION SYSTEM

Abstract

Research in machine translation (MT) is advancing in recent times, however, concentration has been on languages with high number of speakers and abundant digital resources. Unfortunately, some languages, like Yoruba, are often left out. This study focuses on the development of an English to Yoruba machine translation system, addressing the need for a translation system to allow for ease of communication between Yoruba speakers who doesn’t understand the English language. A substantial parallel corpus, primarily sourced from the Menyo-20k dataset, was employed to ensure diverse topic coverage and robust evaluation. The methodology involved data collection, preprocessing, model development, and evaluation using the BLEU metric. The resulting system demonstrated a BLEU score of 11.9, indicating foundational translation capabilities while highlighting the need for further refinement in idiomatic expressions. This work not only contributes to the preservation and promotion of the Yoruba language but also serves as a framework for future research in low-resource language translation systems, emphasizing the importance of cultural sensitivity in technological advancement