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Using hierarchical information structure for prosody prediction in content-to-speech applications

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dc.contributor.author Domínguez Bajo, Mónica
dc.contributor.author Farrús, Mireia
dc.contributor.author Burga Díaz, Alicia
dc.contributor.author Wanner, Leo
dc.date.accessioned 2016-12-13T16:52:11Z
dc.date.available 2016-12-13T16:52:11Z
dc.date.issued 2016
dc.identifier.citation Domínguez M, Farrús M, Burga A, Wanner L. Using hierarchical information structure for prosody prediction in content-to-speech application. In: Proceedings of Speech Prosody 8; 2016 May 31 - Jun 3; Boston, United States. [Boston]: ISCA, 2016. p. 1019-23. DOI: 10.13140/RG.2.1.2643.1128
dc.identifier.issn 2333-2042
dc.identifier.uri http://hdl.handle.net/10230/27753
dc.description Paper presented at Speech Prosody 8, 2016 May 31 - Jun 3; Boston, United States.
dc.description.abstract State-of-the-art prosody modelling in content-to-speech (CTS) applications still uses the same methodology to predict intonation cues as text-to-speech (TTS) applications, namely the analysis of the generated surface sentences with respect to part of speech, syntactic dependency relations and word order. On the other side, several theoretical studies argue that morphology, syntax, and information (or communicative) structure that organizes/na given content (semantic or deep-syntactic structure) with respect to the intention of the speaker show a strong correlation with intonation. However, little empirical work based on sufficiently large corpora has been carried out so far to buttress this argumentation. We present empirical evidence for the Information Structure–Prosody correlation using the Wall Street Journal Penn Treebank corpus recorded by native American English speakers. Our experiments reach a prosody prediction accuracy of 80% using the hierarchical information structure from the Meaning-Text Theory, compared to 59% of the baseline.
dc.description.sponsorship This work is part of a project that has received funding from the European Union’s Horizon 2020 Research and Innovation/nProgramme under the Grant Agreement number H2020-RIA-645012. The second author is partially funded by a grant from/nthe Spanish Ministry of Economy and Competitivity in the framework of the Juan de la Cierva fellowship program.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher International Speech Communication Association (ISCA)
dc.relation.ispartof Proceedings of Speech Prosody 8; 2016 May 31 - Jun 3; Boston, United States. [Boston]: ISCA, 2016. p. 1019-23.
dc.rights © ISCA. The authors retain the rights to any intellectual property developed by the authors and included in the manuscript.
dc.title Using hierarchical information structure for prosody prediction in content-to-speech applications
dc.type info:eu-repo/semantics/conferenceObject
dc.identifier.doi http:dx.doi.org/10.13140/RG.2.1.2643.1128
dc.subject.keyword Information structure
dc.subject.keyword Thematicity
dc.subject.keyword Theme
dc.subject.keyword Rheme
dc.subject.keyword Prosody
dc.subject.keyword Prosodic phrase
dc.subject.keyword ToBI
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/645012
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion


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