Design and Implementation of Gender-Voice Prediction Using Machine Learning

Student: SAMUEL OLUWASEUN ADENIYI (Project, 2025)
Department of Computer Science
Lens Polytechnic, offa, Kwara State.

Abstract

This project revolves around the meticulous development of an advanced Gender Prediction System using state-of-the-art machine learning techniques. The primary objective is to create a sophisticated application capable of accurately determining an individual's gender based on distinctive data features The report comprehensively explores the architecture, functionality, and methodologies employed in crafting this innovative system. The project's significance lies in its potential to contribute to various field gender-specific user experiences, and human-computer interaction. The methodology section outlines a systematic approach to data collection, ensuring ethical considerations and robust feature extraction. The choice and implementation of machine learning algorithms, along with their training procedures and optimization techniques, are thoroughly discussed. The system's architecture, algorithms, and functionalities are elaborated upon in the design and implementation chapter, highlighting the system's sophistication and efficiency in gender- voice prediction. Results and evaluation provide empirical evidence of the system's accuracy, emphasizing its practicality and real-world applicability.

Keywords
design implementation gendervoice prediction machine learning
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