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Speech Enhancement in Wavelet Domain using Principle Component Analysis and Enhancement Filters

by B. Kirubagari, S. Palanivel
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 70 - Number 1
Year of Publication: 2013
Authors: B. Kirubagari, S. Palanivel
10.5120/11928-7705

B. Kirubagari, S. Palanivel . Speech Enhancement in Wavelet Domain using Principle Component Analysis and Enhancement Filters. International Journal of Computer Applications. 70, 1 ( May 2013), 24-28. DOI=10.5120/11928-7705

@article{ 10.5120/11928-7705,
author = { B. Kirubagari, S. Palanivel },
title = { Speech Enhancement in Wavelet Domain using Principle Component Analysis and Enhancement Filters },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 70 },
number = { 1 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 24-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume70/number1/11928-7705/ },
doi = { 10.5120/11928-7705 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:31:43.783376+05:30
%A B. Kirubagari
%A S. Palanivel
%T Speech Enhancement in Wavelet Domain using Principle Component Analysis and Enhancement Filters
%J International Journal of Computer Applications
%@ 0975-8887
%V 70
%N 1
%P 24-28
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The aim of speech enhancement is to improve the perceptual quality and intelligibility of the speech by reducing the background noise. This paper proposes a technique in wavelet domain to enhance the signal. The signal is decomposed into approximation coefficients and detail coefficients which are filtered separately using spectral subtraction and wiener filter. The signal is reconstructed by transforming it into time domain by applying inverse wavelet domain. Wavelet features of the noisy speech signal are extracted and the dimension of the features is reduced using Principle component analysis (PCA). Experiments are conducted on noisy speech signal database (NOIZEUS), which consists of speech signals corrupted by eight different real world noises recorded at different signal-to-noise (SNR) levels. The performance of the proposed algorithm is evaluated using SNR, which is a standard measure of the amount of background noise present in a speech signal and Mean opinion score(MOS) . Experiments results show the increase in the efficiency of the proposed enhancement algorithm.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Speech enhancement PCA Wavelet domain SNR

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