Kernel Principal Component Analysis
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Robust Speaker Identification Using Greedy Kernel PCA
ICTAI '08 Proceedings of the 2008 20th IEEE International Conference on Tools with Artificial Intelligence - Volume 02
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In this paper, we propose a classifier ensemble of various channel compensation and feature enhancement methods for robust speaker identification on various environments. The proposed ensemble system is constructed with 15 classifiers including three channel compensation methods (including CMS and variance normalization, and without compensation) and five feature enhancement methods (including PCA, kernel PCA, greedy kernel PCA, kernel multimodal discriminant analysis, and without enhancement). Experimental results show that the proposed ensemble system gives the highest average speaker identification rate in various environments (channels, noises, and sessions).