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Title:
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Classification of acoustic events using SVM-based clustering schemes
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Author:
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Temko, Andrey A.; Nadeu Camprubí, Climent
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Other authors:
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Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. VEU - Grup de Tractament de la Parla |
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Abstract:
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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
set at each node. With it, a 31.5% relative average error reduction is obtained with respect to the best result from a conventional binary
tree scheme. |
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Abstract:
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Peer Reviewed |
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Subject(s):
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-Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la parla i del senyal acústic
-Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
-Signal processing
-Acoustic event classification
-Support vector machines
-Clustering
-Gaussian processes
-SVM-based clustering
-Sound database
-SVM-based classifier
-Processament del senyal |
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Rights:
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Document type:
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Article |
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Share:
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