A Hybrid HMM-Based Speech Recognizer Using Kernel-Based Discriminants as Acoustic Models

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http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.82

18th International Conference on Patt ...

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	Edin Andelic, Martin Schaffoner, Marcel Katz, Sven E. Kruger, "A Hybrid HMM-Based Speech Recognizer Using Kernel-Based Discriminants as Acoustic Models," Pattern Recognition, International Conference on, vol. 2, pp. 1158-1161, 18th International Conference on Pattern Recognition (ICPR'06) Volume 2, 2006.

	BibTex	x
	@article{ 10.1109/ICPR.2006.82, author = {Edin Andelic and Martin Schaffoner and Marcel Katz and Sven E. Kruger}, title = {A Hybrid HMM-Based Speech Recognizer Using Kernel-Based Discriminants as Acoustic Models}, journal ={Pattern Recognition, International Conference on}, volume = {2}, year = {2006}, issn = {1051-4651}, pages = {1158-1161}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.82}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Pattern Recognition, International Conference on TI - A Hybrid HMM-Based Speech Recognizer Using Kernel-Based Discriminants as Acoustic Models SN - 1051-4651 SP1158 EP1161 A1 - Edin Andelic, A1 - Martin Schaffoner, A1 - Marcel Katz, A1 - Sven E. Kruger, PY - 2006 KW - null VL - 2 JA - Pattern Recognition, International Conference on ER -

Edin Andelic, Cognitive Systems Group, IESK Otto-von-Guericke-University, Germany

Martin Schaffoner, Cognitive Systems Group, IESK Otto-von-Guericke-University, Germany

Marcel Katz, Cognitive Systems Group, IESK Otto-von-Guericke-University, Germany

Sven E. Kruger, Cognitive Systems Group, IESK Otto-von-Guericke-University, Germany

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-based speech recognition system by translating the outputs of the kernel-based classifier into class-conditional probabilities and using them instead of Gaussian mixtures as production probabilities of a HMM-based decoder for speech recognition. The performance of the described hybrid structure is demonstrated on the DARPA Resource Management (RM1) corpus.

Citation:

Edin Andelic, Martin Schaffoner, Marcel Katz, Sven E. Kruger, "A Hybrid HMM-Based Speech Recognizer Using Kernel-Based Discriminants as Acoustic Models," icpr, vol. 2, pp.1158-1161, 18th International Conference on Pattern Recognition (ICPR'06) Volume 2, 2006

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