Type–2 Fuzzy Gaussian mixture models for singing voice classification in commercial music production. (22nd April 2013)

• Record Type: Journal Article
• Authors: Maazouzi, Faiz; Bahi, Halima
• Is Part Of: International journal of signal and imaging systems engineering. Volume 6:Number 2(2013)
• Page Start: 111
• Page End: 118
• Publication Date: 2013-04-22
• Subjects: music information retrieval -- feature extraction -- feature selection -- singing voice classification -- fuzzy Gaussian mixture models -- voice–music separation -- commercial music production -- voice type -- voice quality -- fuzzy modelling; Signal processing -- Periodicals; Imaging systems -- Periodicals; Information theory -- Periodicals; 621.3822
• Languages: English
• ISSNs: 1748-0698

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.