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Classification of acoustic events using SVM-based clustering schemes

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Classification of acoustic events using SVM-based clustering schemes
Acoustic events produced in controlled environments may carry information useful for perceptually aware interfaces. In this paper we focus on the problem of classifying 16 types of meeting-room acoustic events. First of all, we have defined the events and gathered a sound database. Then, several classifiers based on support vector machines (SVM) are developed using confusion matrix based clustering schemes to deal with the multi-class problem. Also, several sets of acoustic features are defined and used in the classification tests. In the experiments, the developed SVM-based classifiers are compared with an already reported binary tree scheme and with their correlative Gaussian mixture model (GMM) classifiers. The best results are obtained with a tree SVM-based classifier that may use a different feature
Andrey Temko, Climent Nadeu
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2006
Where PR
Authors Andrey Temko, Climent Nadeu
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