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Type–2 Fuzzy Gaussian mixture models for singing voice classification in commercial music production

Type–2 Fuzzy Gaussian mixture models for singing voice classification in commercial music production The paper describes a system of singing voice classification in the commercial music productions. A first step in our system is to separate the singer's voice from the music. Based on the vocal part, two sets of parameters are formed, one for singing voice type and the other for the singing voice quality. Each set of parameters contains a number of MPEG–7 low–level descriptors and other descriptors; at the classification stage the paper suggests an extension of Gaussian Mixture Models (GMMs), by using the Type–2 FGMMs (Type–2 Fuzzy Gaussian Mixture Models). Results show substantial improvements when compared to similar works. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Signal and Imaging Systems Engineering Inderscience Publishers

Type–2 Fuzzy Gaussian mixture models for singing voice classification in commercial music production

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References (25)

Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1748-0698
eISSN
1748-0701
DOI
10.1504/IJSISE.2013.053418
Publisher site
See Article on Publisher Site

Abstract

The paper describes a system of singing voice classification in the commercial music productions. A first step in our system is to separate the singer's voice from the music. Based on the vocal part, two sets of parameters are formed, one for singing voice type and the other for the singing voice quality. Each set of parameters contains a number of MPEG–7 low–level descriptors and other descriptors; at the classification stage the paper suggests an extension of Gaussian Mixture Models (GMMs), by using the Type–2 FGMMs (Type–2 Fuzzy Gaussian Mixture Models). Results show substantial improvements when compared to similar works.

Journal

International Journal of Signal and Imaging Systems EngineeringInderscience Publishers

Published: Jan 1, 2013

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