In order to solve the problem that the speech recognition rate in noise environment is used in Mel frequency cepstral coefficients（ MFCC）

an improved feature extraction method based on cochlear filter cepstral coefficient（ CFCC） is proposed. First

extract the characteristic parameters of CFCC has the characteristics of hearing; then

using an improved linear discriminant analysis（ LDA） linear transformation on the characteristic parameters extracted

get more distinguishing characteristic parameters of the diagonalization of the covariance matrix hidden Markov model（ HMM） and meet the needs; finally

the mean variance normalization

get the characteristic parameters of the final. The experimental results show that the proposed method can effectively improve the recognition rate and robustness of speech recognition system in noisy environment.