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Statements

Subject Item
n2:RIV%2F49777513%3A23520%2F14%3A43922838%21RIV15-TA0-23520___
rdf:type
skos:Concept n19:Vysledek
rdfs:seeAlso
http://link.springer.com/chapter/10.1007%2F978-3-319-10816-2_58
dcterms:description
Most modern speech synthesis systems utilize large speech corpora to learn new voices. These speech corpora usually contain several hours of speech spoken by talented speakers who are able to record such an amount of speech data in a sufficient quality. An appropriate phonetic and prosodic annotation of the recorded utterances is necessary for a high quality of synthesized speech. For many languages, the pitch shape within the last prosodic word of a phrase is characteristic for particular types of sentences and phrase structure of compound/complex sentences. However in the real data, this formal convention can be breached and a different pitch shape than expected can be present. This can be a source of prosody inconsistency in synthesized speech. This article presents some experiments on automatic detection of prosodic mismatch in recorded utterances. A simple classifier based on GMM was proposed for this task. Experiments were performed on 5 large speech corpora. The classification results were successfully verified by listening tests. Most modern speech synthesis systems utilize large speech corpora to learn new voices. These speech corpora usually contain several hours of speech spoken by talented speakers who are able to record such an amount of speech data in a sufficient quality. An appropriate phonetic and prosodic annotation of the recorded utterances is necessary for a high quality of synthesized speech. For many languages, the pitch shape within the last prosodic word of a phrase is characteristic for particular types of sentences and phrase structure of compound/complex sentences. However in the real data, this formal convention can be breached and a different pitch shape than expected can be present. This can be a source of prosody inconsistency in synthesized speech. This article presents some experiments on automatic detection of prosodic mismatch in recorded utterances. A simple classifier based on GMM was proposed for this task. Experiments were performed on 5 large speech corpora. The classification results were successfully verified by listening tests.
dcterms:title
Initial Experiments on Automatic Correction of Prosodic Annotation of Large Speech Corpora Initial Experiments on Automatic Correction of Prosodic Annotation of Large Speech Corpora
skos:prefLabel
Initial Experiments on Automatic Correction of Prosodic Annotation of Large Speech Corpora Initial Experiments on Automatic Correction of Prosodic Annotation of Large Speech Corpora
skos:notation
RIV/49777513:23520/14:43922838!RIV15-TA0-23520___
n3:aktivita
n16:P
n3:aktivity
P(ED1.1.00/02.0090), P(TA01011264)
n3:dodaniDat
n9:2015
n3:domaciTvurceVysledku
n8:9516697 n8:1395726
n3:druhVysledku
n20:D
n3:duvernostUdaju
n6:S
n3:entitaPredkladatele
n13:predkladatel
n3:idSjednocenehoVysledku
21866
n3:idVysledku
RIV/49777513:23520/14:43922838
n3:jazykVysledku
n21:eng
n3:klicovaSlova
prosodeme; prosodic annotation; speech corpora
n3:klicoveSlovo
n11:speech%20corpora n11:prosodeme n11:prosodic%20annotation
n3:kontrolniKodProRIV
[9E8475D11736]
n3:mistoKonaniAkce
Brno
n3:mistoVydani
Heidelberg
n3:nazevZdroje
Text, Speech, and Dialogue
n3:obor
n7:JD
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n14:ED1.1.00%2F02.0090 n14:TA01011264
n3:rokUplatneniVysledku
n9:2014
n3:tvurceVysledku
Hanzlíček, Zdeněk Grůber, Martin
n3:typAkce
n10:WRD
n3:zahajeniAkce
2014-09-08+02:00
s:issn
0302-9743
s:numberOfPages
8
n18:doi
10.1007/978-3-319-10816-2_58
n23:hasPublisher
Springer International Publishing
n22:isbn
978-3-319-10815-5
n15:organizacniJednotka
23520