中文摘要：

汉语数字识别常用MFCC作为特征，针对0-9十个数字MFCC样本特征数据量大的问题，提出了用GMM模型对提取的特征参数MFCC的数据进行聚类来减少数据量，以GMM模型参数中的均值作为新的特征，采用动态规划算法进行汉语数字语音识别。仿真实验表明，进行GMM特征变换后的新特征数据为MFCC的30．9％，系统运行时间减少了237．18s，识别率降低1．11％。

英文摘要：

MFCC is widely used in Chinese digital identification. Because the amount of MFCC extracted from 0-9 is too large, the mean of model parameters which is clustered with GMM by MFCC to reduce the amount is employed as a new feature with DTW for Chinese digital identification. Simulation results demonstrate that the amount of the new feature is 30.9% to that of MFCC, the running time reduces by 237.18s, but the recognition rate decreases by 1.11%.