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Description
  • In the presented work we are dealing with modelling and detection of lexical stress-group (foot) for Czech language. Detection of foot as one type of supra-segmental (prosody) information nearly corresponds to detection of word boundaries. Every native speaker is able to distinguish the feet in continuous speech, but on the other hand there are still no obvious connections between the sound qualities (pitch, intensity, syllable length) and foot prominence realization in Czech. In the experiment we tried to train the Hidden Markov Models (HMM) for Czech feet representation using only pitch information in the syllable nuclei. The most of Czech SPEECON database was used as an experiment source database. A necessary part of the presented system is a tool that transforms given Czech text into the foot units according to the known linguistic rules.
  • In the presented work we are dealing with modelling and detection of lexical stress-group (foot) for Czech language. Detection of foot as one type of supra-segmental (prosody) information nearly corresponds to detection of word boundaries. Every native speaker is able to distinguish the feet in continuous speech, but on the other hand there are still no obvious connections between the sound qualities (pitch, intensity, syllable length) and foot prominence realization in Czech. In the experiment we tried to train the Hidden Markov Models (HMM) for Czech feet representation using only pitch information in the syllable nuclei. The most of Czech SPEECON database was used as an experiment source database. A necessary part of the presented system is a tool that transforms given Czech text into the foot units according to the known linguistic rules. (en)
Title
  • Foot Detection in Czech Using Pitch Information and HMM
  • Foot Detection in Czech Using Pitch Information and HMM (en)
skos:prefLabel
  • Foot Detection in Czech Using Pitch Information and HMM
  • Foot Detection in Czech Using Pitch Information and HMM (en)
skos:notation
  • RIV/68407700:21230/13:00207379!RIV14-MSM-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
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
  • 75415
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/13:00207379
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • prosody; stressed-group detection; foot; pitch; clitics absorption; ASR; HMM (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [64425D673B8F]
http://linked.open...v/mistoKonaniAkce
  • Plzeň
http://linked.open...i/riv/mistoVydani
  • Berlin
http://linked.open...i/riv/nazevZdroje
  • Text, Speech, and Dialogue
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Bartošek, Jan
  • Hanžl, Václav
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 0302-9743
number of pages
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 978-3-642-40584-6
http://localhost/t...ganizacniJednotka
  • 21230
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