TEXT-DEPENDENT METHOD FOR GENDER IDENTIFICATION THROUGH SYNTHESIS OF VOICED SEGMENTS

Differences of physiological properties of the glottis and the vocal track 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 gender classification. Acoustics measures of voice sources were extracted from 10 utterances spoken by 20 male and 20 female talkers (aged 19 to 25 year old). Speech long term features, including amplitude, zero crossing rate, short time energy, spectrum flux, and spectrogram is proposed for sex identification. An experimental framework is set-up for these classification task and the result of about 97% for gender classification clearly validate this hypothesis.