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SZŐKE, I., SCHWARZ, P., BURGET, L., KARAFIÁT, M., MATĚJKA, P., ČERNOCKÝ, J.
Originální název
Phoneme Based Acoustics Keyword Spotting in Informal Continuous Speech
Typ
článek v časopise - ostatní, Jost
Jazyk
angličtina
Originální abstrakt
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.
Klíčová slova
acoustic keyword spotting, hidden Markov model, phoneme, recognition network
Autoři
Rok RIV
2005
Vydáno
31. 8. 2005
ISSN
0302-9743
Periodikum
Lecture Notes in Computer Science
Ročník
Číslo
3658
Stát
Spolková republika Německo
Strany od
302
Strany do
309
Strany počet
8
URL
https://www.fit.vutbr.cz/~szoke/papers/tsd_2005.pdf, https://www.fit.vutbr.cz/~szoke/papers/keywordspotting_poster_2005.pdf
BibTex
@article{BUT42913, 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", journal="Lecture Notes in Computer Science", year="2005", volume="2005", number="3658", pages="8", issn="0302-9743", url="https://www.fit.vutbr.cz/~szoke/papers/tsd_2005.pdf, https://www.fit.vutbr.cz/~szoke/papers/keywordspotting_poster_2005.pdf" }