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Description
  • This paper deals with the modification of the rule-based duration model by extending the neural network algorithm incorporated into the TTS system Epos. A particular network predicting the sound duration in Czech declarative sentences read in neutral voice is described. The results show that the network was able to learn the characteristics of the speaker. The output generated by the network is much more natural than the previous one, based on simple rules.
  • This paper deals with the modification of the rule-based duration model by extending the neural network algorithm incorporated into the TTS system Epos. A particular network predicting the sound duration in Czech declarative sentences read in neutral voice is described. The results show that the network was able to learn the characteristics of the speaker. The output generated by the network is much more natural than the previous one, based on simple rules. (en)
  • Tento příspěvek se zabývá modifikací na pravidlech založeného modelu trvání rozšířením systému neuronových sítí zabudovaných v TTS systému Epos. Je zde popsána neuronová síť předpovídající trvání hlásek v českých oznamovacích větách s neutrální prozodií. Výsledky ukazují, že neuronová síť je schopna naučit se charakteristické rysy mluvčího. Trvání generované neuronovou sítí je pak přirozenější než původní, na jednoduchých pravidlech založený, model. (cs)
Title
  • Using neural networks to model duration in Czech text-to-speech synthesis
  • Using neural networks to model duration in Czech text-to-speech synthesis (en)
  • Modelování trvání syntetické češtiny pomocí neuronových sítí (cs)
skos:prefLabel
  • Using neural networks to model duration in Czech text-to-speech synthesis
  • Using neural networks to model duration in Czech text-to-speech synthesis (en)
  • Modelování trvání syntetické češtiny pomocí neuronových sítí (cs)
skos:notation
  • RIV/67985882:_____/05:00021878!RIV08-AV0-67985882
http://linked.open.../vavai/riv/strany
  • 76;83
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(1QS108040569), P(GA102/05/0278), Z(AV0Z20670512)
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
  • 548172
http://linked.open...ai/riv/idVysledku
  • RIV/67985882:_____/05:00021878
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • speech processing; speech synthesis; neural nets (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [A45EF84302E8]
http://linked.open...v/mistoKonaniAkce
  • Praha
http://linked.open...i/riv/mistoVydani
  • Dresden
http://linked.open...i/riv/nazevZdroje
  • Elektronische Sprachsignalverarbeitung
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
  • Horák, Petr
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
issn
  • 0940-6832
number of pages
http://purl.org/ne...btex#hasPublisher
  • TUDpress
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