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Proc. Interspeech

dc.contributor.authorWatts, Oliver
dc.contributor.authorYamagishi, Junichi
dc.contributor.authorKing, Simon
dc.date.accessioned2010-12-22T11:43:51Z
dc.date.available2010-12-22T11:43:51Z
dc.date.issued2010en
dc.identifier.urihttp://hdl.handle.net/1842/4567
dc.description.abstractWe analyse the contribution of higher-level elements of the linguistic specification of a data-driven speech synthesiser to the naturalness of the synthetic speech which it generates. The system is trained using various subsets of the full feature-set, in which features relating to syntactic category, intonational phrase boundary, pitch accent and boundary tones are selectively removed. Utterances synthesised by the different configurations of the system are then compared in a subjective evaluation of their naturalness. The work presented forms background analysis for an ongoing set of experiments in performing text-to-speech (TTS) conversion based on shallow features: features that can be trivially extracted from text. By building a range of systems, each assuming the availability of a different level of linguistic annotation, we obtain benchmarks for our on-going work.en
dc.titleThe role of higher-level linguistic features in HMM-based speech synthesisen
dc.typeConference Paperen
rps.titleProc. Interspeechen
dc.date.updated2010-12-22T11:43:51Z
dc.date.openingDate2010-09-22
dc.date.closingDate2010-09-24


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