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Description
  • Článek je o pokrocích v akustickém modelování pro rozpoznávání češtiny<br> (cs)
  • This paper presents recent advances in Automatic Speech Recognition for the Czech Language. Improvements were achieved both in acoustic and language modeling. We mainly aim on the acoustic part of the issue. The results are presented in two contexts, the lecture recognition and SpeeCon+Temic test set. The paper shows the impact of using advanced modeling techniques such as HLDA, VTLN and CMLLR. On the lecture test set, we show that training acoustic models using word networks together with the pronunciation dictionary gives about 4-5% absolute performance improvement as opposed to using direct phonetic transcriptions. An effect of incorporating the &quot;schwa&quot; phoneme in the training phase shows a slight improvement.
  • This paper presents recent advances in Automatic Speech Recognition for the Czech Language. Improvements were achieved both in acoustic and language modeling. We mainly aim on the acoustic part of the issue. The results are presented in two contexts, the lecture recognition and SpeeCon+Temic test set. The paper shows the impact of using advanced modeling techniques such as HLDA, VTLN and CMLLR. On the lecture test set, we show that training acoustic models using word networks together with the pronunciation dictionary gives about 4-5% absolute performance improvement as opposed to using direct phonetic transcriptions. An effect of incorporating the &quot;schwa&quot; phoneme in the training phase shows a slight improvement. (en)
Title
  • Advances in Acoustic Modeling for the Recognition of Czech
  • Pokrok v akustickém modelování pro rozpoznávání češtiny (cs)
  • Advances in Acoustic Modeling for the Recognition of Czech (en)
skos:prefLabel
  • Advances in Acoustic Modeling for the Recognition of Czech
  • Pokrok v akustickém modelování pro rozpoznávání češtiny (cs)
  • Advances in Acoustic Modeling for the Recognition of Czech (en)
skos:notation
  • RIV/00216305:26230/08:PU76782!RIV09-MV0-26230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(FT-TA3/006), P(VD20072010B16)
http://linked.open...iv/cisloPeriodika
  • 5246
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
  • 355010
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26230/08:PU76782
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Automatic Speech Recognition, LVCSR system, acoustic modeling, HLDA, VTLN, CMLLR, lectures recognition (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • DE - Spolková republika Německo
http://linked.open...ontrolniKodProRIV
  • [AE32CF9A9B73]
http://linked.open...i/riv/nazevZdroje
  • Lecture Notes in Computer Science (IF 0,513)
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...v/svazekPeriodika
  • 2008
http://linked.open...iv/tvurceVysledku
  • Karafiát, Martin
  • Kopecký, Jiří
  • Glembek, Ondřej
issn
  • 0302-9743
number of pages
http://localhost/t...ganizacniJednotka
  • 26230
is http://linked.open...avai/riv/vysledek of
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