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Description
  • When adapting an existing speech recognition system to a new language, major development costs are associated with the creation of an appropriate acoustic model (AM). For its training, a certain amount of recorded and annotated speech is required. In this paper, we show that not only the annotation process, but also the process of speech acquisition can be automated to minimize the need of human and expert work. We demonstrate the proposed methodology on Croatian language, for which the target AM has been built via cross-lingual adaptation of a Czech AM in 2 ways: a) using the commercially available GlobalPhone database, and b) by automatic speech data mining from HRT radio archive. The latter approach is cost-free, yet it yields comparable or better results in experiments conducted on 3 Croatian test sets.
  • When adapting an existing speech recognition system to a new language, major development costs are associated with the creation of an appropriate acoustic model (AM). For its training, a certain amount of recorded and annotated speech is required. In this paper, we show that not only the annotation process, but also the process of speech acquisition can be automated to minimize the need of human and expert work. We demonstrate the proposed methodology on Croatian language, for which the target AM has been built via cross-lingual adaptation of a Czech AM in 2 ways: a) using the commercially available GlobalPhone database, and b) by automatic speech data mining from HRT radio archive. The latter approach is cost-free, yet it yields comparable or better results in experiments conducted on 3 Croatian test sets. (en)
Title
  • Cost-Efficient Development of Acoustic Models for Speech Recognition of Related Languages
  • Cost-Efficient Development of Acoustic Models for Speech Recognition of Related Languages (en)
skos:prefLabel
  • Cost-Efficient Development of Acoustic Models for Speech Recognition of Related Languages
  • Cost-Efficient Development of Acoustic Models for Speech Recognition of Related Languages (en)
skos:notation
  • RIV/46747885:24220/13:#0002793!RIV14-GA0-24220___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GPP103/11/P499), P(TA01011204)
http://linked.open...iv/cisloPeriodika
  • 3
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
  • 67190
http://linked.open...ai/riv/idVysledku
  • RIV/46747885:24220/13:#0002793
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Speech recognition; acoustic model; cross-lingual adaptation; Slavic languages (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • CZ - Česká republika
http://linked.open...ontrolniKodProRIV
  • [3C881643F9E5]
http://linked.open...i/riv/nazevZdroje
  • Radioengineering
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
  • 22
http://linked.open...iv/tvurceVysledku
  • Nouza, Jan
  • Červa, Petr
  • Kuchařová, Michaela
http://linked.open...ain/vavai/riv/wos
  • 000324900200026
issn
  • 1210-2512
number of pages
http://localhost/t...ganizacniJednotka
  • 24220
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