Gender voice classification with huge accuracy rate

Mustafa Sahib Shareef (Al Muthanna University)
Thulfiqar Abd (Al Muthanna University)
Yaqeen S. Mezaal (Al-Esraa University College)

TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 18, No 5: October 2020

Gender voice recognition stands for an imperative research field in acoustics and speech processing as human voice shows very remarkable aspects. This study investigates speech signals to devise a gender classifier by speech analysis to forecast the gender of the speaker by investigating diverse parameters of the voice sample. A database has 2270 voice samples of celebrities, both male and female. Through Mel frequency cepstrum coefficient (MFCC), vector quantization (VQ), and machine learning algorithm (J 48), an accuracy of about 100% is achieved by the proposed classification technique based on data mining and Java script.