Abstract
A speaker recognition method based on support vector and multi-scale wavelet analysis is proposed and a frame model of it is constructed in this paper. Firstly, Multi-scale wavelet analysis is applied to the process of signal preprocess, based on it, the theory of multi-scale analysis is applied to separate speech and noise, and enhance the speech consequently. Secondly, in the feature extracting phase, Mel Frequency Cepstrum Coefficient and its difference are derived to be the characteristic parameters and then composed into feature vector sequences based on SVM. Finally, a multi-category SVM algorithm is applied to realize the speaker classification and recognition by making training and testing based on swatches.
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