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ICML
2003
IEEE
16 years 15 days ago
Discriminative Gaussian Mixture Models: A Comparison with Kernel Classifiers
We show that a classifier based on Gaussian mixture models (GMM) can be trained discriminatively to improve accuracy. We describe a training procedure based on the extended Baum-W...
Aldebaro Klautau, Nikola Jevtic, Alon Orlitsky
ICPR
2006
IEEE
16 years 24 days ago
A Hybrid HMM-Based Speech Recognizer Using Kernel-Based Discriminants as Acoustic Models
In this paper we propose a novel order-recursive training algorithm for kernel-based discriminants which is computationally efficient. We integrate this method in a hybrid HMM-bas...
Edin Andelic, Marcel Katz, Martin Schafföner,...
ICASSP
2011
IEEE
14 years 3 months ago
A partial least squares framework for speaker recognition
Modern approaches to speaker recognition (verification) operate in a space of “supervectors” created via concatenation of the mean vectors of a Gaussian mixture model (GMM) a...
Balaji Vasan Srinivasan, Dmitry N. Zotkin, Ramani ...
ICPR
2008
IEEE
15 years 6 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
ICASSP
2010
IEEE
14 years 12 months ago
Statistical approach to enhancing esophageal speech based on Gaussian mixture models
This paper presents a novel method of enhancing esophageal speech using statistical voice conversion. Esophageal speech is one of the alternative speaking methods for laryngectome...
Hironori Doi, Keigo Nakamura, Tomoki Toda, Hiroshi...