论文首先介绍了传统的语音特征参数MFCC，它是基于人耳听觉

特性设计的一种特征参数，在静音环境下能得到较高的识别率，但在

信噪比较低时识别率急剧下降，不利于实用化。本文通过对MFCC算

法的分析和研究，发现其中的FFT和DCT在整个时频空间使用固定的

。分析窗，这不符合语音信号特性，而小波变换具有多分辨率特性，更

符合人耳的听觉特性。因此，本文将小波变换和MFCC算法相结合，

提出了三种新的语音识别特-Speech recognition has wide use in the field of communication and so

on·Speech feature parameter extraction is an important part of the speech

recognition system．The performance of the feature parameter haftuences

the system’S performance directly．And the environmental noise is a kev

factor of restricting the performance of the feature parameter．This paper，s

research object is extracting the speech feature parameter under the noise

environment·Then it analyzes the auditory model of human，deeply

analyzes and researches the traditional speech feature parameter MFCC，

and proposes three improved MFCC parameters based on theⅥ，avelet

transformation and the auditory characteristic ofhuman．Besides，the paper

also gives all improved method about the feature parameter ZCPA．