Přístupnostní navigace
E-application
Search Search Close
Publication detail
SZŐKE, I., SCHWARZ, P., BURGET, L., KARAFIÁT, M., MATĚJKA, P., ČERNOCKÝ, J.
Original Title
Phoneme Based Acoustics Keyword Spotting in Informal Continuous Speech
Type
journal article - other
Language
English
Original Abstract
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.
Keywords
acoustic keyword spotting, hidden Markov model, phoneme, recognition network
Authors
RIV year
2005
Released
31. 8. 2005
ISBN
0302-9743
Periodical
Lecture Notes in Computer Science
Year of study
Number
3658
State
Federal Republic of Germany
Pages from
302
Pages to
309
Pages count
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" }