Doc. Dr. Ing. Jan Černocký
| Szőke, I., Schwarz, P., Burget, L., Karafiát, M., Matějka, P., Černocký, J.: Phoneme Based Acoustics Keyword Spotting in Informal Continuous Speech, In: Lecture Notes in Computer Science, Vol. 2005, No. 3658, DE, p. 8, ISSN 0302-9743 | | Publication language: | english |
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| Original title: | Phoneme Based Acoustics Keyword Spotting in Informal Continuous Speech |
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| Title (cs): | Fonémový detektor klíčových slov založený na akustice pro neformální konverzační řeč |
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| Pages: | 8 |
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| Place: | DE |
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| Year: | 2005 |
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| Journal: | Lecture Notes in Computer Science, Vol. 2005, No. 3658, DE |
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| ISSN: | 0302-9743 |
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| URL: | https://www.fit.vutbr.cz/~szoke/papers/tsd_2005.pdf [PDF] |
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| URL: | https://www.fit.vutbr.cz/~szoke/papers/keywordspotting_poster_2005.pdf [PDF] |
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| Keywords |
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| acoustic keyword spotting, hidden Markov model, phoneme, recognition network |
| Annotation |
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| This paper describes several ways of acoustic keywords spotting (KWS),
based on Gaussian mixture model (GMM) hidden Markov models (HMM) and
phoneme posterior probabilities from FeatureNet. Context-independent
and dependent phoneme models are used in the GMM/HMM system. The
systems were trained and evaluated on informal continuous speech. We
used different complexities of KWS recognition network and different
types of phoneme models. We study the impact of these parameters on the
accuracy and computational complexity, and conclude that phoneme
posteriors outperform conventional GMM/HMM system. |
| BibTeX: |
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@ARTICLE{
author = {Igor Szőke and Petr Schwarz and Lukáš Burget and Martin
Karafiát and Pavel Matějka and Jan Černocký},
title = {Phoneme Based Acoustics Keyword Spotting in Informal
Continuous Speech},
pages = {8},
journal = {Lecture Notes in Computer Science},
volume = {2005},
number = {3658},
year = {2005},
ISSN = {0302-9743},
language = {english},
url = {http://www.fit.vutbr.cz/research/view_pub.php?id=7882}
} |
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