Doc. Ing. Lukáš Burget, Ph.D.

POVEY Daniel, BURGET Lukáš, AGARWAL Mohit, AKYAZI Pinar, FENG Kai, GHOSHAL Arnab, GLEMBEK Ondřej, GOEL Nagendra K., KARAFIÁT Martin, RASTROW Ariya, ROSE Richard, SCHWARZ Petr and THOMAS Samuel. Subspace Gaussian mixture models for speech recognition. In: Proc. International Conference on Acoustics, Speech, and Signal Processing. Dallas: IEEE Signal Processing Society, 2010, pp. 4330-4333. ISBN 978-1-4244-4296-6. ISSN 1520-6149.
Publication language:english
Original title:Subspace Gaussian mixture models for speech recognition
Title (cs):Sub-space gaussovské modely pro rozpoznávání řeči
Pages:4330-4333
Proceedings:Proc. International Conference on Acoustics, Speech, and Signal Processing
Conference:International Conference on Acoustics, Speech, and Signal Processing 2010
Place:Dallas, US
Year:2010
ISBN:978-1-4244-4296-6
Journal:Proc. International Conference on Acoustics, Speech, and Signal Processing, Vol. 2010, No. 3, Piscataway, US
ISSN:1520-6149
Publisher:IEEE Signal Processing Society
URL:http://www.fit.vutbr.cz/research/groups/speech/publi/2010/povey_icassp2010_4330.pdf [PDF]
Keywords
Speech Recognition, Hidden Markov Models, Gaussian Mixture Models
Annotation
The paper is on subspace Gaussian mixture models for speech recognition. We describe an acoustic modeling approach in which all phonetic states share a common GMM structure.
Abstract
We describe an acoustic modeling approach in which all phonetic states share a common Gaussian Mixture Model structure, and the means and mixture weights vary in a subspace of the total parameter space. We call this a Subspace Gaussian Mixture Model (SGMM). Globally shared parameters define the subspace. This style of acoustic model allows for a much more compact representation and gives better results than a conventional modeling approach, particularly with smaller amounts of training data.
BibTeX:
@INPROCEEDINGS{
   author = {Daniel Povey and Luk{\'{a}}{\v{s}} Burget and
	Mohit Agarwal and Pinar Akyazi and Kai Feng and
	Arnab Ghoshal and Ond{\v{r}}ej Glembek and K.
	Nagendra Goel and Martin Karafi{\'{a}}t and Ariya
	Rastrow and Richard Rose and Petr Schwarz and
	Samuel Thomas},
   title = {Subspace Gaussian mixture models for speech
	recognition},
   pages = {4330--4333},
   booktitle = {Proc. International Conference on Acoustics, Speech, and
	Signal Processing},
   journal = {Proc. International Conference on Acoustics, Speech, and
	Signal Processing},
   volume = {2010},
   number = {3},
   year = {2010},
   location = {Dallas, US},
   publisher = {IEEE Signal Processing Society},
   ISBN = {978-1-4244-4296-6},
   ISSN = {1520-6149},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php?id=9311}
}

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