Publication Details

Subspace Gaussian mixture models for speech recognition

POVEY, D.; BURGET, L.; AGARWAL, M.; AKYAZI, P.; FENG, K.; GHOSHAL, A.; GLEMBEK, O.; GOEL, N.; KARAFIÁT, M.; RASTROW, A.; ROSE, R.; SCHWARZ, P.; THOMAS, S. Subspace Gaussian mixture models for speech recognition. Proc. International Conference on Acoustics, Speech, and Signal Processing. Proc. International Conference on Acoustics, Speech, and Signal Processing. Dallas: IEEE Signal Processing Society, 2010. p. 4330-4333. ISBN: 978-1-4244-4296-6. ISSN: 1520-6149.
Czech title
Sub-space gaussovské modely pro rozpoznávání řeči
Type
conference paper
Language
English
Authors
Povey Daniel
Burget Lukáš, doc. Ing., Ph.D. (DCGM)
Agarwal Mohit
Akyazi Pinar
Feng Kai
Ghoshal Arnab
Glembek Ondřej, Ing., Ph.D.
Goel Nagendra
Karafiát Martin, Ing., Ph.D. (DCGM)
Rastrow Ariya
Rose Richard
Schwarz Petr, Ing., Ph.D. (DCGM)
Thomas Samuel
URL
Keywords

Speech Recognition, Hidden Markov Models, Gaussian Mixture Models

Abstract

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.

Annotation

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.

Published
2010
Pages
4330–4333
Journal
Proc. International Conference on Acoustics, Speech, and Signal Processing, vol. 2010, no. 3, ISSN 1520-6149
Proceedings
Proc. International Conference on Acoustics, Speech, and Signal Processing
ISBN
978-1-4244-4296-6
Publisher
IEEE Signal Processing Society
Place
Dallas
BibTeX
@inproceedings{BUT37026,
  author="Daniel {Povey} and Lukáš {Burget} and Mohit {Agarwal} and Pinar {Akyazi} and Kai {Feng} and Arnab {Ghoshal} and Ondřej {Glembek} and Nagendra {Goel} and Martin {Karafiát} and Ariya {Rastrow} and Richard {Rose} and Petr {Schwarz} and Samuel {Thomas}",
  title="Subspace Gaussian mixture models for speech recognition",
  booktitle="Proc. International Conference on Acoustics, Speech, and Signal Processing",
  year="2010",
  journal="Proc. International Conference on Acoustics, Speech, and Signal Processing",
  volume="2010",
  number="3",
  pages="4330--4333",
  publisher="IEEE Signal Processing Society",
  address="Dallas",
  isbn="978-1-4244-4296-6",
  issn="1520-6149",
  url="http://www.fit.vutbr.cz/research/groups/speech/publi/2010/povey_icassp2010_4330.pdf"
}
Back to top