Ing. Martin Karafiát, Ph.D.
| Povey, D., Karafiát, M., Ghoshal, A., Schwarz, P.: A Symmetrization of the Subspace Gaussian Mixture Model, In: Proceedings of 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, Praha, CZ, IEEESP, 2011, s. 4504-4507, ISBN 978-1-4577-0537-3 | | Jazyk publikace: | angličtina |
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| Název publikace: | A Symmetrization of the Subspace Gaussian Mixture Model |
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| Název (cs): | Symetrizace Subspace Gaussian Mixture Modelů |
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| Strany: | 4504-4507 |
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| Sborník: | Proceedings of 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing |
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| Konference: | International Conference on Acoustics, Speech and Signal Processing 2011 |
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| Místo vydání: | Praha, CZ |
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| Rok: | 2011 |
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| ISBN: | 978-1-4577-0537-3 |
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| Vydavatel: | IEEE Signal Processing Society |
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| URL: | http://www.fit.vutbr.cz/research/groups/speech/publi/2011/povey_icassp2011_4504.pdf [PDF] |
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| Klíčová slova |
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| Speech Recognition, Hidden Markov Models, Subspace Gaussian Mixture Models |
| Anotace |
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| Publikace pojednává o symetrizaci Subspace Gaussian Mixture Modelu. Autoři článku popisují modifikaci SGMM modelu, kterou nazývají Symetric SGMM. |
| Abstrakt |
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| Last year we introduced the Subspace Gaussian Mixture Model (SGMM), and we demonstrated Word Error Rate improvements on a fairly small-scale task. Here we describe an extension to the SGMM, which we call the symmetric SGMM. It makes the model fully symmetric between the "speech-state vectors" and "speaker vectors" by making the mixture weights depend on the speaker as well as the speech state. We had previously avoided this as it introduces difficulties for efficient likelihood evaluation and parameter estimation, but we have found a way to overcome those difficulties. We find that the symmetric SGMM can give a very worthwhile improvement over the previously described model. We will also describe some larger-scale experiments with the SGMM, and report on progress toward releasing open-source software that supports SGMMs. |
| BibTeX: |
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@INPROCEEDINGS{
author = {Daniel Povey and Martin Karafiát and Arnab Ghoshal and Petr
Schwarz},
title = {A Symmetrization of the Subspace Gaussian Mixture Model},
pages = {4504--4507},
booktitle = {Proceedings of 2011 IEEE International Conference on
Acoustics, Speech, and Signal Processing},
year = {2011},
location = {Praha, CZ},
publisher = {IEEE Signal Processing Society},
ISBN = {978-1-4577-0537-3},
language = {english},
url = {http://www.fit.vutbr.cz/research/view_pub.php?id=9652}
} |
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