Excellence in Research and Innovation for Humanity
%0 Journal Article
%A S. Souli and  Z. Lachiri
%D 2012 
%J  International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering
%B World Academy of Science, Engineering and Technology
%I International Science Index 68, 2012
%T Multiclass Support Vector Machines for Environmental Sounds Classification Using log-Gabor Filters
%U http://waset.org/publications/7948
%V 68
%X In this paper we propose a robust environmental sound classification approach, based on spectrograms features driven from log-Gabor filters. This approach includes two methods. In the first methods, the spectrograms are passed through an appropriate log-Gabor filter banks and the outputs are averaged and underwent an optimal feature selection procedure based on a mutual information criteria. The second method uses the same steps but applied only to three patches extracted from each spectrogram.

To investigate the accuracy of the proposed methods, we conduct experiments using a large database containing 10 environmental sound classes. The classification results based on Multiclass Support Vector Machines show that the second method is the most efficient with an average classification accuracy of 89.62 %.

%P 857 - 861