%0 Journal Article
	%A M. A. Ben Messaoud and  A. Bouzid and  N. Ellouze
	%D 2015
	%J International Journal of Electronics and Communication Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 97, 2015
	%T Automatic Segmentation of the Clean Speech Signal
	%U https://publications.waset.org/pdf/10000638
	%V 97
	%X Speech Segmentation is the measure of the change
point detection for partitioning an input speech signal into regions
each of which accords to only one speaker. In this paper, we apply
two features based on multi-scale product (MP) of the clean speech,
namely the spectral centroid of MP, and the zero crossings rate of
MP. We focus on multi-scale product analysis as an important tool
for segmentation extraction. The MP is based on making the product
of the speech wavelet transform coefficients (WTC). We have
estimated our method on the Keele database. The results show the
effectiveness of our method. It indicates that the two features can find
word boundaries, and extracted the segments of the clean speech.

	%P 114 - 117