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Detail publikačního výsledku
POVEY, D.; KARAFIÁT, M.; GHOSHAL, A.; SCHWARZ, P.
Originální název
A Symmetrization of the Subspace Gaussian Mixture Model
Anglický název
Druh
Stať ve sborníku mimo WoS a Scopus
Originální abstrakt
We have described a modification to the Subspace Gaussian Mixture Model which we call the Symmetric SGMM. This is a very natural extension which removes an asymmetry in the way the Gaussian mixture weights were previously computed. The extra computation is minimal but the memory used for the acoustic model is nearly doubled. Our experimental results were inconsistent: on one setup we got a large improvement of 1.5% absolute, and on another setup it was much smaller.
Anglický abstrakt
Klíčová slova
Speech Recognition, Hidden Markov Models, Subspace Gaussian Mixture Models
Klíčová slova v angličtině
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Rok RIV
2012
Vydáno
22.05.2011
Nakladatel
IEEE Signal Processing Society
Místo
Praha
ISBN
978-1-4577-0537-3
Kniha
Proceedings of 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing
Strany od
4504
Strany do
4507
Strany počet
4
URL
http://www.fit.vutbr.cz/research/groups/speech/publi/2011/povey_icassp2011_4504.pdf
BibTex
@inproceedings{BUT76375, author="Daniel {Povey} and Martin {Karafiát} and Arnab {Ghoshal} and Petr {Schwarz}", title="A Symmetrization of the Subspace Gaussian Mixture Model", booktitle="Proceedings of 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing", year="2011", pages="4504--4507", publisher="IEEE Signal Processing Society", address="Praha", isbn="978-1-4577-0537-3", url="http://www.fit.vutbr.cz/research/groups/speech/publi/2011/povey_icassp2011_4504.pdf" }