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Multi-class classifier of non-speech audio based
on Fisher kernel |
| Rongyan WANG,Gang LIU,Jun GUO,Yu FANG, |
| Pattern Recognition
and Intelligent System Laboratory, Beijing University of Posts and
Telecommunications, Beijing 100876, China; |
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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.
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| Keywords
Fisher kernel
support vector machine (SVM)
Gaussian mixture model (GMM)
mixture clustering
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Issue Date: 05 March 2010
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