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  • This paper deals with the method of voice activity detection. Rising requirements to applications with variable-rate speech coding also increases the role of voice activity detectors which become crucial for the efficient bandwidth reduction. The paper aims especially to two detector types; these are the detector based on short-time signal energy and statistical model-based voice activity detector. Decision-making rules of the statistical model-based detector are derived from the LRT (Likelihood Ratio TTest) by estimating unknown parameters using the ML (Maximum Likelihood) criterion. In addition there is an effective hang-over scheme based on HMM (Hidden Markov Model) principles in the detector. There were models for these detectors created in Matlab simulation environment. Models were tested on voice signals with the white noise as well as real noises. The results were evaluated and compared for various types of noises and SNR (Signal to Noise Ratios) values.
  • This paper deals with the method of voice activity detection. Rising requirements to applications with variable-rate speech coding also increases the role of voice activity detectors which become crucial for the efficient bandwidth reduction. The paper aims especially to two detector types; these are the detector based on short-time signal energy and statistical model-based voice activity detector. Decision-making rules of the statistical model-based detector are derived from the LRT (Likelihood Ratio TTest) by estimating unknown parameters using the ML (Maximum Likelihood) criterion. In addition there is an effective hang-over scheme based on HMM (Hidden Markov Model) principles in the detector. There were models for these detectors created in Matlab simulation environment. Models were tested on voice signals with the white noise as well as real noises. The results were evaluated and compared for various types of noises and SNR (Signal to Noise Ratios) values. (en)
  • Příspěvek se věnuje metodám detekce řečového signálu. Se vzrůstajícím počtem aplikací širokopásmového kódování řeči se zvyšuje úloha detektorů řečové aktivity s ohledem na dosažení co nejužšího pásma. Příspěvek se zaměřuje na dva typy detektorů; je to detektor založený na sledování krátkodobé energie signálu a detektor založený na statistických metodách. Rozhodovací pravidlo statistického detektoru je odvozeno od testu maximální podobnosti LRT (Likelihood Ratio Test), kdy neznámé parametry jsou odhadnutty metodou maximální podobnosti ML (Maximum Likelihood). Navíc je doplněn efektivním modelem přechodu mezi řečovými a šumovými segmenty založeným na skrytých Markovových řetězcích. Oba detektory byly simulovány v prostředí Matlab a byly testovány na různých nahrávkách obsahujících umělé i reálné hluky pro různé poměry signálu od šumu. (cs)
Title
  • Voice Activity Detection based-on Statistic Models
  • Voice Activity Detection based-on Statistic Models (en)
  • Detektor řečové aktivity založený na statistických metodách (cs)
skos:prefLabel
  • Voice Activity Detection based-on Statistic Models
  • Voice Activity Detection based-on Statistic Models (en)
  • Detektor řečové aktivity založený na statistických metodách (cs)
skos:notation
  • RIV/00216305:26220/05:PU51360!RIV06-GA0-26220___
http://linked.open.../vavai/riv/strany
  • 175-180
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(1ET301710509), P(GA102/04/1097), Z(MSM0021630513)
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
  • 549680
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26220/05:PU51360
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • voice activity detector statistical model (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [D502D18135FD]
http://linked.open...v/mistoKonaniAkce
  • Prague, Lichenstein Palace
http://linked.open...i/riv/mistoVydani
  • Prague, Czech Republic
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the 16th Conference Electronic Speech Signal Processing
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
  • Sysel, Petr
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
  • Ústav radiotechniky a elektroniky AV ČR
https://schema.org/isbn
  • 3-938863-17-X
http://localhost/t...ganizacniJednotka
  • 26220
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