关键词: 语音识别, 小波包变换, 特征提取, Mel频率倒谱系数

Abstract: Through the analysis and research of Mel-Frequency Cepstral Coefficient（MFCC），can discover the limitation of using Fast Fourier Transform（FFT） which takes fix window width in the entire time and frequency space.It doesn’t match the characteristic of speech signal.But the wavelet transformation has the multi-resolution characteristic and can better conform to the auditory characteristic of human.This paper proposes a new speech recognition method DWPTMFCC of dynamic and static feature integration.Wavelet Packet Transformation（WPT） method is introduced to feature parameters in virtue of MFCC，then combines difference feature formed dynamic and static feature parameter integration.The simulation results show that the recognition rate is better using the new features than using MFCC in noise environment，especially in low SNR（Signal Noise Ratio）.

Key words: speech recognition, Wavelet Packet Transform（WPT）, feature extraction, Mel-Frequency Cepstral Coefficient（MFCC）