title: Gender classification in children based on speech characteristics: using fundamental and formant frequencies of Malay vowels.
abstract: Speech is one of the prevalent communication mediums for humans. Identifying the gender of a child speaker based on his/her speech is crucial in telecommunication and speech therapy. This article investigates the use of fundamental and formant frequencies from sustained vowel phonation to distinguish the gender of Malay children aged between 7 and 12 years. The Euclidean minimum distance and multilayer perceptron were used to classify the gender of 360 Malay children based on different combinations of fundamental and formant frequencies (F0, F1, F2, and F3). The Euclidean minimum distance with normalized frequency data achieved a classification accuracy of 79.44%, which was higher than that of the nonnormalized frequency data. Age-dependent modeling was used to improve the accuracy of gender classification. The Euclidean distance method obtained 84.17% based on the optimal classification accuracy for all age groups. The accuracy was further increased to 99.81% using multilayer perceptron based on mel-frequency cepstral coefficients.
authors.affiliation: Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Lembah Pantai, Kuala Lumpur, Malaysia. alireza.zourmand@siswa.um.edu.my
authors.forename: Alireza
authors.initials: A
authors.lastname: Zourmand
authors.forename: Hua-Nong
authors.initials: HN
authors.lastname: Ting
authors.forename: Seyed Mostafa
authors.initials: SM
authors.lastname: Mirhassani
mesh_terms: D000367:Age Factors; D000465:Algorithms; D002648:Child; D002663:Child Language; D005260:Female; D006801:Humans; D008296:Malaysia; D008297:Male; D008390:Markov Chains; D016571:Neural Networks, Computer; D010699:Phonation; D010700:Phonetics; D012737:Sex Factors; D012815:Signal Processing, Computer-Assisted; D013061:Speech Acoustics; D013068:Speech Production Measurement; D013997:Time Factors; D014833:Voice Quality