Mixture of experts for audio classification: an application to male female classification and musical genre recognition

Author

Harb, Hadi ; Chen, Liming ; Auloge, Jean-Yves

Author_Institution

Dept. Mathematiques Informatique, Ecole Centrale de Lyon

Volume

2

fYear

2004

fDate

30-30 June 2004

Firstpage

1351

Abstract

We report the experimental results obtained when applying a mixture of experts to the problem of audio classification for multimedia applications. The mixture of experts is based on multilayer perceptron neural networks as individual experts and piecewise Gaussian modeling was used for audio signal representation. Experimental results on two audio classification problems, male/female classification and musical genre recognition, show a clear improvement in using a mixture of experts in comparison to one individual expert

Keywords

Gaussian processes; audio signal processing; expert systems; learning (artificial intelligence); multilayer perceptrons; multimedia systems; pattern recognition; signal classification; signal representation; audio classification; audio signal representation; individual experts; male-female classification; mixture of experts; multilayer perceptron; multimedia applications; musical genre recognition; neural networks; piecewise Gaussian modeling; training process; Context modeling; Covariance matrix; Frequency; Humans; Neural networks; Neurons; Psychoacoustic models; Psychology; Signal representations; Training data;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia and Expo, 2004. ICME '04. 2004 IEEE International Conference on

Conference_Location

Taipei

Print_ISBN

0-7803-8603-5

Type

conf

DOI

10.1109/ICME.2004.1394479

Filename

1394479