The role of voice source measures on automatic gender classification

Abstract

Differences of physiological properties of the glottis and the vocal tract are partly due to age and/or gender differences. Since these differences are reflected in the speech signal, acoustic measures related to those properties can be helpful for automatic age and gender classification. In this paper, the focus is on the role of acoustic measures related to the voice source in automatic gender classification, implemented using Support Vector Machines (SVMs). Acoustic measures of the vocal tract and the voice source were extracted from 3880 utterances spoken by 205 male and 160 female talkers (aged 8 to 39 years old). Formant frequencies and formant bandwidths were used as vocal tract measures, and open quotient and source spectral tilt correlates were used as voice source measures. Results show that the addition of voice source measures can help improve automatic gender classification results for most age groups.