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
Original title:Phoneme Based Acoustics Keyword Spotting in Informal Continuous Speech
Title (cs):Fonémový detektor klíčových slov založený na akustice pro neformální konverzační řeč
Pages:8
Place:DE
Year:2005
Journal:Lecture Notes in Computer Science, Vol. 2005, No. 3658, DE
ISSN:0302-9743
URL:https://www.fit.vutbr.cz/~szoke/papers/tsd_2005.pdf [PDF]
URL:https://www.fit.vutbr.cz/~szoke/papers/keywordspotting_poster_2005.pdf [PDF]
Keywords
acoustic keyword spotting, hidden Markov model, phoneme, recognition network
Annotation
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:
@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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