Time-frequency methods for enhancing speech

Owen Patrick Kenny; Douglas J. Nelson

doi:10.1117/12.284192

24 October 1997 Time-frequency methods for enhancing speech

Owen Patrick Kenny, Douglas J. Nelson

Proceedings Volume 3162, Advanced Signal Processing: Algorithms, Architectures, and Implementations VII; (1997) https://doi.org/10.1117/12.284192
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

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.

Citation Download Citation

Owen Patrick Kenny and Douglas J. Nelson "Time-frequency methods for enhancing speech", Proc. SPIE 3162, Advanced Signal Processing: Algorithms, Architectures, and Implementations VII, (24 October 1997); https://doi.org/10.1117/12.284192

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