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Automatic syllabification for danish text-to-speech systems

2009Conference object Restricted access
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dc.contributor.authorBeck, Jeppe
dc.contributor.authorBraga, Daniela
dc.contributor.authorNogueira, João
dc.contributor.authorSales-Dias, Miguel
dc.contributor.authorCoelho, Luís
dc.date.accessioned2016-02-05T12:43:16Z
dc.date.available2016-02-05T12:43:16Z
dc.date.issued2009
dc.description.abstractIn this paper, a rule-based automatic syllabifier for Danish is described using the Maximal Onset Principle. Prior success rates of rule-based methods applied to Portuguese and Catalan syllabification modules were on the basis of this work. The system was implemented and tested using a very small set of rules. The results gave rise to 96.9% and 98.7% of word accuracy rate, contrary to our initial expectations, being Danish a language with a complex syllabic structure and thus difficult to be rule-driven. Comparison with data-driven syllabification system using artificial neural networks showed a higher accuracy rate of the former system.pt_PT
dc.identifier.isbn978-1-61567-692-7
dc.identifier.urihttp://hdl.handle.net/10400.22/7635
dc.language.isoengpt_PT
dc.publisherInternational Speech Communication Associationpt_PT
dc.relation.publisherversionhttp://www.isca-speech.org/archive/interspeech_2009/i09_1287.htmlpt_PT
dc.subjectAutomatic syllabificationpt_PT
dc.subjectRule-based techniquespt_PT
dc.subjectArtificial neural networkspt_PT
dc.subjectText-to-speechpt_PT
dc.titleAutomatic syllabification for danish text-to-speech systemspt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceBrighton, Englandpt_PT
oaire.citation.endPage1294pt_PT
oaire.citation.startPage1291pt_PT
oaire.citation.titleINTERSPEECH 2009: Annual Conference of the International Speech Communication Association, 10thpt_PT
person.familyNameCoelho
person.givenNameLuís
person.identifier.orcid0000-0001-7123-0450
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication7927657d-8c14-4754-bde9-e5b6d45b8435
relation.isAuthorOfPublication.latestForDiscovery7927657d-8c14-4754-bde9-e5b6d45b8435

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