Blind phone segmentation based on spectral change detection using Legendre polynomial approximation.

Abstract

Phone segmentation involves partitioning a continuous speech signal into discrete phone units. In this paper, a method for automatic phone segmentation without prior knowledge of speech content is proposed. The signal spectrum was represented by band-energies. A segment of the band-energy curve was approximated using Legendre polynomial expansion, allowing Legendre polynomial coefficients to describe the properties of the segment. The spectral changes, which imply phone boundaries in the speech signal, were then detected by monitoring the variations of Legendre polynomial coefficients. A two-step algorithm for detecting phone boundaries was derived. The first step was to detect phone boundaries using first-order and second-order coefficients of the Legendre polynomial approximation. The second step was to locate slow spectral changes in the regions of concatenated voiced phones using zero-order coefficients of the Legendre polynomial approximation. This enabled the phone boundaries missed during the first step to be recovered. An evaluation using the TIMIT corpus indicated that the proposed method is comparable to or more accurate than previous methods.