Journal of Dinda : Data Science, Information Technology, and Data Analytics
Vol 1 No 1 (2021): February

Pengenalan Jenis Kelamin Manusia Berbasis Suara Menggunakan MFCC dan GMM

Faisal Dharma Adhinata (Institut Teknologi Telkom Purwokerto)
Diovianto Putra Rakhmadani (Institut Teknologi Telkom Purwokerto)
Alon Jala Tirta Segara (Institut Teknologi Telkom Purwokerto)



Article Info

Publish Date
02 Feb 2021

Abstract

Biometric information that exists in humans is unique from one human to another. One of the biometric data that is easily obtained is the human voice. The human voice is identic data that can differentiate between individuals. When we hear human voices directly, it is easy for our ears to tell the person who is speaking is male or female. But sometimes male voices can resemble girls and vice versa. Therefore, we propose a human voice detection system through Artificial Intelligence (AI) in machine learning. In this study, we used the Mel Frequency Cepstrum Coefficients (MFCC) method to extract human voice features and Gaussian Mixture Models (GMM) for the classification of female or male voice data. The experiment results showed that the system built was able to detect human gender through biometric voice data with an accuracy of 81.18%.

Copyrights © 2021






Journal Info

Abbrev

dinda

Publisher

Subject

Computer Science & IT

Description

Journal of Dinda : Data Science, Information Technology, and Data Analytics as a publication media for research results in the fields of Data Science, Information Technology, and Data Analytics, but not implicitly limited. Published 2 times a year in February and August. The journal is managed by ...