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Multilanguage speech-based gender classification using time-frequency features and SVM classifier

Wani, Taiba and Gunawan, Teddy Surya and Mansor, Hasmah and Ahmad Qadri, Syed Asif and Sophian, Ali and Ambikairajah, Eliathamby and Ihsanto, Eko (2020) Multilanguage speech-based gender classification using time-frequency features and SVM classifier. In: The 2nd International Conference on Innovative Technology, Engineering and Sciences 2020 (iCITES 2020), 22nd December 2020, Pekan, Pahang. (Unpublished)

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Speech is the most significant communication mode among human beings and a potential method for human-computer interaction (HCI). Being unparallel in complexity, the perception of human speech is very hard. The most crucial characteristic of speech is gender, and for the classification of gender often pitch is utilized. However, it is not a reliable method for gender classification as in numerous cases, the pitch of female and male is nearly similar. In this paper, we propose a time-frequency method for the classification of gender-based on the speech signal. Various techniques like framing, Fast Fourier Transform (FFT), auto-correlation, filtering, power calculations, speech frequency analysis, and feature extraction and formation are applied on speech samples. The classification is done based on features derived from the frequency and time domain processing using the Support Vector Machines (SVM) algorithm. SVM is trained on two speech databases Berlin Emo-DB and IITKGP-SEHSC, in which a total of 400 speech samples are evaluated. An accuracy of 83% and 81% for IITKGP-SEHSC and Berlin Emo-DB have been observed, respectively.

Item Type: Conference or Workshop Item (Plenary Papers)
Additional Information: 5588/86116 Virtually hosted by Universiti Malaysia Pahang
Uncontrolled Keywords: Gender Classification, Pre-processing, Fast-Fourier Transform (FFT), Support Vector Machine (SVM).
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User: Dr Teddy Surya Gunawan
Date Deposited: 30 Dec 2020 16:58
Last Modified: 30 Dec 2020 16:59
URI: http://irep.iium.edu.my/id/eprint/86116

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