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Please use this identifier to cite or link to this item: http://hdl.handle.net/1842/4567

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Title: The role of higher-level linguistic features in HMM-based speech synthesis
Authors: Watts, Oliver
Yamagishi, Junichi
King, Simon
Issue Date: 2010
Journal Title: Proc. Interspeech
Abstract: We 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.
URI: http://hdl.handle.net/1842/4567
Appears in Collections:CSTR publications

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