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Description
  • Filter bank approach is commonly used in feature extraction phase of speech recognition (e.g. Mel frequency cepstral coefficients). Filter bank is applied for modification of magnitude spectrum according to physiological and psychological findings. However, since mechanism of human auditory system is not fully understood,the optimal filter bank parameters are not known. This work presents a method where the filter bank, optimized for discriminability between phonemes, is derived directly from phoneticaally labeled speech data using Linear Discriminant Analysis. This work can be seen as another proof of the fact that incorporation of psychoacoustic findings into feature extraction can lead to better recognition performance.
  • Filter bank approach is commonly used in feature extraction phase of speech recognition (e.g. Mel frequency cepstral coefficients). Filter bank is applied for modification of magnitude spectrum according to physiological and psychological findings. However, since mechanism of human auditory system is not fully understood,the optimal filter bank parameters are not known. This work presents a method where the filter bank, optimized for discriminability between phonemes, is derived directly from phoneticaally labeled speech data using Linear Discriminant Analysis. This work can be seen as another proof of the fact that incorporation of psychoacoustic findings into feature extraction can lead to better recognition performance. (en)
Title
  • Data Driven Design of Filter Bank for Speech Recognition
  • Data Driven Design of Filter Bank for Speech Recognition (en)
skos:prefLabel
  • Data Driven Design of Filter Bank for Speech Recognition
  • Data Driven Design of Filter Bank for Speech Recognition (en)
skos:notation
  • RIV/00216305:26220/01:PU23539!RIV/2002/MSM/262202/N
http://linked.open.../vavai/riv/strany
  • 299-304
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM 262200011)
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
  • 676907
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26220/01:PU23539
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • mel filterbank, speech recognition, linear discriminant analysis (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [9160F30A85D5]
http://linked.open...v/mistoKonaniAkce
  • Zelezna Ruda
http://linked.open...i/riv/mistoVydani
  • Zelezna Ruda
http://linked.open...i/riv/nazevZdroje
  • Proc. 4th Intl. Conference Text, Speech Dialogue
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...ocetUcastnikuAkce
http://linked.open...nichUcastnikuAkce
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Burget, Lukáš
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
  • Springer-Verlag
https://schema.org/isbn
  • 3-540-42557-8
http://localhost/t...ganizacniJednotka
  • 26220
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