The Design and Implementation of a Nlp Model to Solve Language Barriers in the Heaithcare Sector

Student: Oluwaferanmi Omoyemi Ogunmola (Project, 2025)
Department of Computer and Information Science
Bamidele Olumilua University of Edu. Science and Tech. Ikere Ekiti, Ekiti State

Abstract

Speech has been widely known as the primary mode of communication among individuals and computers. The existence of technology brought about human-computer interfaces to allow human-computer interaction. While speech recognition systems have been developed rapidly over the last few years, many challenges have been encountered, such as language barrier, speech rate, environmental conditions, channel, and context of utterance. To enhance the power of speech recognition systems, it is required to design speech recognizers in local languages. There is a lot of development and research in the field of foreign languages but to enhance its power and utility for native people, it’s essential to use this technology in native languages. In this paper, we employ language modeling focusing on the Yoruba language for the task of recognizing speech and also converting the speech to text by constructing sequential MFCC features from the frames of the audio sample. The result shows that using transformer models with features log-mel spectrogram and feature extraction provide a solution to the problem of recognizing speech and also converting the speech to text with an accuracy of 70%.

Keywords
NLP MODEL.
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