基于 Fisher 比的 Bark 小波包变换的语音特征提取算法.

In order to solve the problem of low recognition rate of MFCC parameter, a feature extraction algorithm based on the Bark wavelet packet transform with Fisher is put forward. Firstly, wavelet packet transform is used to construct Bark filter, which can replace the triangular Mel filter. According to the Fisher criterion, feature parameters filtered by Bark filter are adopted, removing the interference information and saving the time of feature matching. Simulation results show that the algorithm is able to enhance the recognition rate and robustness. [ABSTRACT FROM AUTHOR]