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Proceedings Paper

Time-frequency methods for enhancing speech
Author(s): Owen Patrick Kenny; Douglas J. Nelson
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Paper Abstract

Speech signals have the property that they are broad-band white conveying information at a very low rate. The resulting signal has a time-frequency representation which is redundant and slowly varying in both time and frequency. In this paper, a new method for separating speech from noise and interference is presented. This new method uses image enhancement techniques applied to time- frequency representations of the corrupted speech signal. The image enhancement techniques are based on the assumption that speech and/or the noise and interference may be locally represented as a mixture of two-dimensional Gaussian distributions. The signal surface is expanded using a Hermite polynomial expansion and the signal surface is separated from the noise surface by a principal- component process. a Wiener gain surface is calculated from the enhanced image, and the enhanced signal is reconstructed from the Wiener gain surface using a time varying filter constructed from a basis of prolate-spheroidal filters.

Paper Details

Date Published: 24 October 1997
PDF: 10 pages
Proc. SPIE 3162, Advanced Signal Processing: Algorithms, Architectures, and Implementations VII, (24 October 1997); doi: 10.1117/12.284192
Show Author Affiliations
Owen Patrick Kenny, Defence Science and Technology Organisation (Australia)
Douglas J. Nelson, Dept. of Defence (United States)


Published in SPIE Proceedings Vol. 3162:
Advanced Signal Processing: Algorithms, Architectures, and Implementations VII
Franklin T. Luk, Editor(s)

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