Development of a Language Translator Model for Yoruba Language Using Bidirectional Long Short-term Memory Encoder

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dc.contributor.authorAjao, Jumoke Falilat
dc.contributor.authorAjao, Olorundare Abdulazeez
dc.contributor.authorIsiaka, Mope Rafiu
dc.contributor.authorYusuff, Ronke Shakirat
dc.contributor.authorYahaya, Abdullahi
dc.date.accessioned2026-05-16T19:47:14Z
dc.date.available2026-05-16T19:47:14Z
dc.date.issued2024-11-01
dc.description.abstractNigeria is a nation of vast ethnic diversity, encompassing a multitude of cultures, languages, and values. These differences often present significant communication barriers among its various ethnic groups. To bring the language barrier, Google has integrated several Nigerian languages into its translation model. This study focuses on the development of an automatic speech recognition (ASR) system for Yoruba, one of Nigeria’s indigenous languages. Speech dataset was collected from native Yoruba speakers and subjected to extensive preprocessing to eliminate background noise introduced during the recording process. The preprocessed data was then transformed into a speech spectrogram, serving as input to a bidirectional long short-term memory (BiLSTM) model. The hyperparameters of the BiLSTM model were optimised for improved performance. The translation model was evaluated using metrics such as BLEU, METEOR, and ROUGUE. Results demonstrated significant improvements in the ASR model’s ability to accurately transcribe and translate Yoruba language speech. This advancement in translation accuracy highlights the potential for better cross-linguistic communication among Nigeria’s ethnic groups, fostering greater inclusivity and understanding. This study contributes to ongoing efforts to incorporate underrepresented languages in global translation models, addressing the challenge of language diversity in multilingual societies.
dc.identifier.issn3092-8796
dc.identifier.urihttps://kwasuspace.kwasu.edu.ng/handle/123456789/7242
dc.language.isoen
dc.publisherKWASU Journal of Information, Communication and Technology (KJICT.)
dc.titleDevelopment of a Language Translator Model for Yoruba Language Using Bidirectional Long Short-term Memory Encoder
dc.typeArticle
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