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Statements

Subject Item
n2:RIV%2F49777513%3A23520%2F02%3A00071531%21RIV%2F2003%2FMSM%2F235203%2FN
rdf:type
skos:Concept n19:Vysledek
dcterms:description
This paper presents an experimental German speech synthesis system. As in case of a Czech text-to-speech system ARTIC, statistical approach (using hidden Markov models) was employed to build a speech segment database. This approach was confirmed to be language independent and it was shown to be capable of designing a quality database that led to an intelligible synthetic speech of a high quality. Some experiments with clustering the similar speech contexts were performed to enhance the quality of the synthetic speech. Our results show the superiority of phoneme-level clustering to subphoneme-level one. This paper presents an experimental German speech synthesis system. As in case of a Czech text-to-speech system ARTIC, statistical approach (using hidden Markov models) was employed to build a speech segment database. This approach was confirmed to be language independent and it was shown to be capable of designing a quality database that led to an intelligible synthetic speech of a high quality. Some experiments with clustering the similar speech contexts were performed to enhance the quality of the synthetic speech. Our results show the superiority of phoneme-level clustering to subphoneme-level one.
dcterms:title
German and czech speech synthesis using HMM-based speech segment database German and czech speech synthesis using HMM-based speech segment database
skos:prefLabel
German and czech speech synthesis using HMM-based speech segment database German and czech speech synthesis using HMM-based speech segment database
skos:notation
RIV/49777513:23520/02:00071531!RIV/2003/MSM/235203/N
n3:strany
0
n3:aktivita
n18:Z
n3:aktivity
Z(MSM 235200004)
n3:dodaniDat
n7:2003
n3:domaciTvurceVysledku
n6:7014600 n6:4396855 n6:5347947 n6:1922564
n3:druhVysledku
n13:D
n3:duvernostUdaju
n20:S
n3:entitaPredkladatele
n4:predkladatel
n3:idSjednocenehoVysledku
647123
n3:idVysledku
RIV/49777513:23520/02:00071531
n3:jazykVysledku
n12:eng
n3:klicovaSlova
speech synthesis;hidden Markov models;clustering
n3:klicoveSlovo
n5:clustering n5:hidden%20Markov%20models n5:speech%20synthesis
n3:kontrolniKodProRIV
[81EBD2B4AC16]
n3:mistoKonaniAkce
Neuveden
n3:mistoVydani
Neuveden
n3:nazevZdroje
German and czech speech synthesis using HMM-based speech segment database
n3:obor
n16:JD
n3:pocetDomacichTvurcuVysledku
4
n3:pocetTvurcuVysledku
4
n3:pocetUcastnikuAkce
0
n3:pocetZahranicnichUcastnikuAkce
0
n3:rokUplatneniVysledku
n7:2002
n3:tvurceVysledku
Psutka, Josef Tihelka, Daniel Matoušek, Jindřich Hesová, Jana
n3:typAkce
n11:CST
n3:zahajeniAkce
2002-01-01+01:00
n3:zamer
n17:MSM%20235200004
s:numberOfPages
1
n8:hasPublisher
Neuveden
n10:organizacniJednotka
23520