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Title:Evaluation of Signal Processing Methods for Speech Enhancement
Author(s):Dubey, Mahika
Contributor(s):Smaragdis, Paris
Subject(s):Signal processing
Speech enhancement
Abstract:This thesis explores some of the main approaches to the problem of speech signal enhancement. Traditional signal processing techniques including spectral subtraction, Wiener filtering, and subspace methods are very widely used and can produce very good results, especially in the cases of constant ambient noise, or noise that is predictable over the course of the signal. We first study these methods and their results, and conclude with an analysis of the successes and failures of each. Comparisons are based on the effectiveness of the methods of removing disruptive noise, the speech quality and intelligibility of the enhanced signals, and whether or not they introduce some new artifacts into the signal. These characteristics are analyzed using the perceptual evaluation of speech quality (PESQ) measure, the segmental signal-to-noise ratio (SNR), the log likelihood ratio (LLR), and weighted spectral slope distance.
Issue Date:2016-05
Date Available in IDEALS:2016-06-29

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