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Description
  • This paper is about a method for visual segmentation of TV news. The TV news shows are segmented according to the visual stream from the video TV recordings in this method. Human faces are found in the single visual segments with the help of the fast algorithm for face detection. The found faces are compared with the visual GMMs, that have been trained from the video picture of the single broadcasters (anchors) from the TV news. The single visual segments, where the faces of the broadcasters have been found and recognized, have been compared with the acoustic segments from the acoustic segmentation. The speaker adapted HMMs have been used for speech recognition of these acoustic segments. The recognition rate is better for the use of this speaker-adapted HMMs compared to the use of the speaker independent HMMs.
  • This paper is about a method for visual segmentation of TV news. The TV news shows are segmented according to the visual stream from the video TV recordings in this method. Human faces are found in the single visual segments with the help of the fast algorithm for face detection. The found faces are compared with the visual GMMs, that have been trained from the video picture of the single broadcasters (anchors) from the TV news. The single visual segments, where the faces of the broadcasters have been found and recognized, have been compared with the acoustic segments from the acoustic segmentation. The speaker adapted HMMs have been used for speech recognition of these acoustic segments. The recognition rate is better for the use of this speaker-adapted HMMs compared to the use of the speaker independent HMMs. (en)
Title
  • Visual Speech Segmentation and Speaker Recognition for Transcription of TV News
  • Visual Speech Segmentation and Speaker Recognition for Transcription of TV News (en)
skos:prefLabel
  • Visual Speech Segmentation and Speaker Recognition for Transcription of TV News
  • Visual Speech Segmentation and Speaker Recognition for Transcription of TV News (en)
skos:notation
  • RIV/46747885:24220/06:#0001343!RIV10-GA0-24220___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA102/05/0278)
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
  • 506183
http://linked.open...ai/riv/idVysledku
  • RIV/46747885:24220/06:#0001343
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Visual speech segmentation (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [6387CAD5EE5A]
http://linked.open...v/mistoKonaniAkce
  • Pittsburgh, USA
http://linked.open...i/riv/mistoVydani
  • Pittsburgh, USA
http://linked.open...i/riv/nazevZdroje
  • INTERSPEECH 2006 AND 9TH INTERNATIONAL CONFERENCE ON SPOKEN LANGUAGE 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
  • Chaloupka, Josef
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • ISCA-INST SPEECH COMMUNICATION ASSOC
https://schema.org/isbn
  • 978-1-60423-449-7
http://localhost/t...ganizacniJednotka
  • 24220
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