Research articles

Multi-class classifier of non-speech audio based on Fisher kernel

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  • Pattern Recognition and Intelligent System Laboratory, Beijing University of Posts and Telecommunications, Beijing 100876, China;

Published date: 05 Mar 2010

Abstract

Traditional multi-class classification methods based on Fisher kernel combine generative models such as Gaussian mixture models (GMMs) of all the classes together. However, the combination generates high dimensional feature vectors and leads to large computation. In this paper, a new classification method is proposed. This method adopts an intelligent feature space selection strategy by clustering similar Gaussian mixtures in order to reduce the feature dimensions. Audio classification experiments show that the proposed method is more accurate and effective with less computation compared with traditional methods.

Cite this article

Rongyan WANG, Gang LIU, Jun GUO, Yu FANG, . Multi-class classifier of non-speech audio based on Fisher kernel[J]. Frontiers of Electrical and Electronic Engineering, 2010 , 5(1) : 72 -76 . DOI: 10.1007/s11460-009-0073-3

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