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Description
  • Kombinování řečových příznaků použitím vyhlazené heteroscedastické diskriminační analýzy<br> (cs)
  • Feature combination techniques based on PCA, LDA and HLDA are compared in experiments where limited amount of training data is available. Success with feature combination can be quite dependent on proper estimation of statistics required by the used technique. Insufficiency of training data is, therefore, an important problem, which has to be taken in to account in our experiments.<br>Besides of some standard approaches increasing robustness of statistic estimation, methods based on combination of LDA aand HLDA are proposed. An improved recognition performance obtained using these methods is demonstrated in experiments.
  • Feature combination techniques based on PCA, LDA and HLDA are compared in experiments where limited amount of training data is available. Success with feature combination can be quite dependent on proper estimation of statistics required by the used technique. Insufficiency of training data is, therefore, an important problem, which has to be taken in to account in our experiments.<br>Besides of some standard approaches increasing robustness of statistic estimation, methods based on combination of LDA aand HLDA are proposed. An improved recognition performance obtained using these methods is demonstrated in experiments. (en)
Title
  • Kombinování řečových příznaků použitím vyhlazené heteroscedastické diskriminační analýzy (cs)
  • Combination of Speech Features Using Smoothed Heteroscedastic Linear Discriminant Analysis
  • Combination of Speech Features Using Smoothed Heteroscedastic Linear Discriminant Analysis (en)
skos:prefLabel
  • Kombinování řečových příznaků použitím vyhlazené heteroscedastické diskriminační analýzy (cs)
  • Combination of Speech Features Using Smoothed Heteroscedastic Linear Discriminant Analysis
  • Combination of Speech Features Using Smoothed Heteroscedastic Linear Discriminant Analysis (en)
skos:notation
  • RIV/00216305:26230/04:PU49151!RIV/2005/GA0/262305/N
http://linked.open.../vavai/riv/strany
  • 2549-2552
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA102/02/0124)
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
  • 558078
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26230/04:PU49151
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • speech recognition, LDA, HLDA, feature extraction, feature combination<br> (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [087439D1EBFE]
http://linked.open...v/mistoKonaniAkce
  • Jeju Island
http://linked.open...i/riv/mistoVydani
  • Jeju island
http://linked.open...i/riv/nazevZdroje
  • Proc. 8th International Conference on Spoken Language Processing
http://linked.open...in/vavai/riv/obor
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http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Burget, Lukáš
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 1225-4111
number of pages
http://purl.org/ne...btex#hasPublisher
  • Sunjin Printing Co,
http://localhost/t...ganizacniJednotka
  • 26230
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