A speaker recognition system based on an auditory model and neural nets: Performance at different levels of sound pressure and of gaussian white noise

Abstract

This paper performs the assessment of an auditory model based on a human nonlinear cochlear filter-bank and on Neural Nets. The efficiency of this system in speaker recognition tasks has been tested at different levels of voice pressure and different levels of noise. The auditory model yields five psychophysical parameters with which a neural network is trained. We used a number of Spanish words from the 'Ahumada' database as uttered by native male speakers. © 2011 Springer-Verlag Berlin Heidelberg.