Speaker recognition based on a bio-inspired auditory model: Influence of its components, sound pressure and noise level

Abstract

In the present work an assessmet of the influence of the different components that form a bioinspired auditory model in the speaker recognition performance by means of neuronal networks, at different sound pressure levels and Gaussian white noise of the voice signal, was made. The speaker voice is processed through three variants of an auditory model. From its output, a set of psychophysical parameters is extracted, with which neuronal networks for speaker recognition will be trained. Furthermore, the aim is to compare three standardization methods of parameters. As a conclusion, we can observed how psycophysical parameters characterize the speaker with acceptable rates of recognition; the typology of auditory model has influence on speaker recognition. © 2011 Springer-Verlag Berlin Heidelberg.