Applying wavelet analysis to speech segmentation and classification

Abstract

We propose the design of a hearing aid based on the wavelet transform. The fast wavelet transform is used to decompose speech into different frequency components. This paper presents the difficulties in the use of wavelet transforms for speech processing and shows how the careful selection of wavelet coefficients can enable the four major categories of speech - voiced speech, plosives, fricatives, and silence - to be identified. With knowledge of these four categories, it is shown how speech can be easily and effectively segmented.