Gender Detection by Acoustic Characteristics of Sound with Machine Learning Algorithms

Year 2023, , 24 - 28, 30.06.2023

Hamit Mızrak , Serpil Aslan

https://doi.org/10.46572/naturengs.1294655

Cited By: 1

Abstract

Sound has been studied in almost every field since the existence of humans, and sound science branches have emerged due to its increasing importance day by day. Sound has been studied in many fields from the past to the present, and it has become an essential factor in people's understanding of each other. It is possible to determine the voice of individuals with the help of computers in the digitalized world to determine the speech acoustics and the gender of that voice and to determine it with the prediction algorithms in machine learning by utilizing the characteristics of the voice's characteristic metric performance criteria. In this study, six different machine learning algorithms were used. By comparing these machine learning algorithms, prediction results were obtained to determine the best prediction result and the gender difference by using the voice characteristics of individuals.

Keywords

Sound Acoustics, Sound Characteristics, Gender Detection, Machine learning, Hertz

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