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ICASSP
2011
IEEE
12 years 9 months ago
Soft frame margin estimation of Gaussian Mixture Models for speaker recognition with sparse training data
—Discriminative Training (DT) methods for acoustic modeling, such as MMI, MCE, and SVM, have been proved effective in speaker recognition. In this paper we propose a DT method fo...
Yan Yin, Qi Li
TASLP
2008
105views more  TASLP 2008»
13 years 5 months ago
Optimizing the Performance of Spoken Language Recognition With Discriminative Training
The performance of spoken language recognition system is typically formulated to reflect the detection cost and the strategic decision points along the detection-error-tradeoff cur...
Donglai Zhu, Haizhou Li, Bin Ma, Chin-Hui Lee
ICPR
2000
IEEE
14 years 6 months ago
Invariant Image Object Recognition Using Mixture Densities
In this paper we present a mixture density based approach to invariant image object recognition. We start our experiments using Gaussian mixture densities within a Bayesian classi...
Daniel Keysers, Hermann Ney, Jörg Dahmen, Mar...
ICPR
2008
IEEE
13 years 12 months ago
Boosting Gaussian mixture models via discriminant analysis
The Gaussian mixture model (GMM) can approximate arbitrary probability distributions, which makes it a powerful tool for feature representation and classification. However, it su...
Hao Tang, Thomas S. Huang