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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control)
Mustafa Sahib Shareef
Al Muthanna University
Computer Science & IT

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Gender voice classification with huge accuracy rate Mustafa Sahib Shareef; Thulfiqar Abd; Yaqeen S. Mezaal
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 5: October 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i5.13717

Abstract

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.
Co-Authors Thulfiqar Abd Yaqeen S. Mezaal