About: HMM and EHMM Based Voice Activity Detectors and Design of Testing Platform for VAD Classification     Goto   Sponge   NotDistinct   Permalink

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Description
  • The usage of LR and ergodic Markov models in voice activity detection and VAD testing platform is presented in this article. These detectors based on HMMs and EHMMs reach better results than traditional energy or cepstral detectors. The testing of suggested algorithms were realized with data recorded in running car and the contribution is evident especially in this very noisy environment. Commonly with the results of experiment the selection of the data and the design of the VAD testing platform is described in this paper. Used speech records consists of isolated digits, different commands, names and were recorded in environment of quiet car without engine, running car or standing car with running engine.
  • The usage of LR and ergodic Markov models in voice activity detection and VAD testing platform is presented in this article. These detectors based on HMMs and EHMMs reach better results than traditional energy or cepstral detectors. The testing of suggested algorithms were realized with data recorded in running car and the contribution is evident especially in this very noisy environment. Commonly with the results of experiment the selection of the data and the design of the VAD testing platform is described in this paper. Used speech records consists of isolated digits, different commands, names and were recorded in environment of quiet car without engine, running car or standing car with running engine. (en)
Title
  • HMM and EHMM Based Voice Activity Detectors and Design of Testing Platform for VAD Classification
  • HMM and EHMM Based Voice Activity Detectors and Design of Testing Platform for VAD Classification (en)
skos:prefLabel
  • HMM and EHMM Based Voice Activity Detectors and Design of Testing Platform for VAD Classification
  • HMM and EHMM Based Voice Activity Detectors and Design of Testing Platform for VAD Classification (en)
skos:notation
  • RIV/68407700:21230/08:00149485!RIV10-MSM-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA102/08/0707), P(GD102/08/H008), Z(MSM6840770014)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 370338
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/08:00149485
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • EHMM; HMM; VAD; ergodic hidden Markov models; voice activity detection (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [68CDF6EE3504]
http://linked.open...v/mistoKonaniAkce
  • Žilina
http://linked.open...i/riv/mistoVydani
  • Žilina
http://linked.open...i/riv/nazevZdroje
  • Digital Technologies 2008
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Pollák, Petr
  • Tatarinov, Jiří
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • Žilinská univerzita v Žiline. Elektrotechnická fakulta
https://schema.org/isbn
  • 978-80-8070-953-2
http://localhost/t...ganizacniJednotka
  • 21230
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