Properties of auditory model representations
Fernando Perdigão, Luís Sá · 1997
We address the problem of robustness of auditory models as front ends for speech recognition. Auditory models have been referred as superior front ends when speech is corrupted by noise or linear filtering, but there is not yet a deep understanding of its functioning. We analyze some commonly used auditory models and show that they present some interesting properties which are useful for robust speech recognition. In our view, the short-time adaptation provided by hair cell models is a key factor for this robustness. A disadvantage of auditory models is that the distributions of the obtained features are not well represented by gaussian pdfs. We discuss the problem of parameter transformation in order to use a standard recognizer based on CDHMMs with gaussian pdfs and present some digit recognition experiments. 1. INTRODUCTION Several studies have been presented comparing the performance of auditory models with traditional signal processing techniques such as cepstral processing (e....