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Description
  • A method of speaker verification based on Gaussian mixture models is presented in this paper. The method works with a background model which is composed of several submodels. Several different approaches for construction of the background model from the submodels are introduced here: the log likelihood of the background model is determined either as the average of the log likelihoods of the particular submodels, or a maximum from the log likelihoods of the particular submodels is selected. A large number of experiments was performed in order to find which of the approaches gives the best result. All experiments show that procedures which use a maximum of the log likelihoods of the background submodels have better performance than the procedure which uses the average log likelihood.
  • A method of speaker verification based on Gaussian mixture models is presented in this paper. The method works with a background model which is composed of several submodels. Several different approaches for construction of the background model from the submodels are introduced here: the log likelihood of the background model is determined either as the average of the log likelihoods of the particular submodels, or a maximum from the log likelihoods of the particular submodels is selected. A large number of experiments was performed in order to find which of the approaches gives the best result. All experiments show that procedures which use a maximum of the log likelihoods of the background submodels have better performance than the procedure which uses the average log likelihood. (en)
  • V článku je prezentována metoda verifikace řečníka využívající Gaussovských hustotních směsí. Metoda využívá model okolí složený z několika submodelů. V článku jsou uvedeny různé přístupy pro konstrukci složeného modelu: logaritmus pravděpodobnosti složeného modelu je určen buď jako průměr logaritmů pravděpodobností dílčích submodelů, a nebo jako maximum z logaritmů pravděpodobností dílčích submodelů. Provedené experimety ukázaly, že prvně jmenovaný přístup umožňuje dosáhnout lepších výsledků. (cs)
Title
  • Konstrukce modelu okolí pro verifikaci řečníka využívající GMM (cs)
  • On the background model construction for speaker verification using GMM
  • On the background model construction for speaker verification using GMM (en)
skos:prefLabel
  • Konstrukce modelu okolí pro verifikaci řečníka využívající GMM (cs)
  • On the background model construction for speaker verification using GMM
  • On the background model construction for speaker verification using GMM (en)
skos:notation
  • RIV/49777513:23520/04:00000034!RIV07-GA0-23520___
http://linked.open.../vavai/riv/strany
  • 425
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA102/02/0124), Z(MSM 235200004)
http://linked.open...iv/cisloPeriodika
  • 0
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
  • 577840
http://linked.open...ai/riv/idVysledku
  • RIV/49777513:23520/04:00000034
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • speaker verification, score normalization, background model (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • DE - Spolková republika Německo
http://linked.open...ontrolniKodProRIV
  • [CED1F2430B37]
http://linked.open...i/riv/nazevZdroje
  • Lecture Notes in Artificial Intelligence
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
  • Padrta, Aleš
  • Radová, Vlasta
http://linked.open...n/vavai/riv/zamer
issn
  • 0302-9743
number of pages
http://localhost/t...ganizacniJednotka
  • 23520
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