Detail publikace

Phoneme Based Acoustics Keyword Spotting in Informal Continuous Speech

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

SZŐKE, I., SCHWARZ, P., BURGET, L., KARAFIÁT, M., MATĚJKA, P., ČERNOCKÝ, J.

Rok RIV

2005

Vydáno

31. 8. 2005

ISSN

0302-9743

Periodikum

Lecture Notes in Computer Science

Ročník

2005

Číslo

3658

Stát

Spolková republika Německo

Strany od

302

Strany do

309

Strany počet

8

URL

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"
}