Research on False Points Removing of Speech Segmentation

In speech signal processing, the techniques of speech segmentation as front end of preprocessing have great importance in speech enhancing, coding and recognition. This paper analyzes the performances of several typical algorithms of speech segmentation, which are compared with each other. It put emphasis on the study of the algorithm based on the wavelet transformation. The smooth and gradual changing low frequency component can not segment the speech efficiently. In order to solve the problem, this paper put forward to an algorithm based on the cumulate energy of the wavelet transformation which promotes the precision of the segmentation on the phoneme level. But as a result of the wavelet sensitivity, it will present certain number of false spots. Therefore this paper proposes tow methods removing false spots. Finally it makes certain summary to these technologies.