سال انتشار: ۱۳۹۱

محل انتشار: بیستمین کنفرانس مهندسی برق ایران

تعداد صفحات: ۴

نویسنده(ها):

Masoud Geravanchizadeh – University of Tabriz
Alireza Abadianfard –

چکیده:

This paper uses a new set of feature vectors that is based on modulation spectrum of cepstral coefficients by means of Laguerre regression method. The performance of theproposed method is investigated by a gender classification of a noisy speech. Compared with other regression methods, ourproposed feature set demonstrates high performance in the sense of gender classification. Low classification errors obtained in different noisy scenarios proves the superiority ofthe new feature vectors for the classification task.