Computational auditory model and its application in robust speech signal recognition

A computational auditory model is designed based on hearing perception mechanisms,and speech feattire can be extracted by this basic model.This paper is made up of two parts,in the first part,based on the model,an auditory representation as AFCC (Auditory Frequency Cepstral Coefficient) is proposed,thus the vector dimensions can be compressed by this method,also decorrelate each dimensions of the vector.Also a low pass filter is used to simulate the long temporal integration effect of auditory central system.With this low pass filter,new auditory spectrum is extracted,experiments show,the new feature AFCC have high robustness than traditional feature MFCC under HMM recognition system.In the second part,A very simple but efficient model of lateral inhibition is proposed based on lateral inhibition mechanism of auditory perception.MFCCI can be gotten if MFCC is processed by this model,the new representation shows high robustness in speech recognition experiment.AFCCI can be gotten if AFCC is processed by this model,the new represelltation also shows high robustness in speech recognition experiment.