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    %0 Journal Article
    %A Obin, Nicolas
    %A Lanchantin, Pierre
    %T Symbolic Modeling of Prosody: From Linguistics to Statistics
    %D 2015
    %B IEEE/ACM Transactions on Audio, Speech and Language Processing
    %V 3
    %N 23
    %P 588-599
    %F Obin15a
    %K text-to-speech synthesis
    %K speech prosody
    %K speaking style
    %K prosodic events
    %K surface/deep syntactic parsing
    %K hierarchical HMMs
    %K segmental HMMs
    %K Dempster-Shafer fusion
    %X The assignment of prosodic events (accent and phrasing) from the text is crucial in text-to-speech synthesis systems. This paper addresses the combination of linguistic and metric constraints for the assignment of prosodic events in textto- speech synthesis. First, a linguistic processing chain is used to provide a rich linguistic description of a text. Then, a novel statistical representation based on a hierarchical HMM (HHMM) is used to model the prosodic structure of a text: the root layer represents the text, each intermediate layer a sequence of intermediate phrases, the pre-terminal layer the sequence of accents, and the terminal layer the sequence of linguistic contexts. For each intermediate layer, a segmental HMM and information fusion are used to fuse the linguistic and metric constraints for the segmentation of a text into phrases. A set of experiments conducted on multi-speaker databases with various speaking styles reports that: the rich linguistic representation improves drastically the assignment of prosodic events, and the fusion of linguistic and metric constraints significantly improves over standard methods for the segmentation of a text into phrases. These constitute substantial advances that can be further used to model the speech prosody of a speaker, a speaking style, and emotions for text-to-speech synthesis.
    %1 1
    %2 1
    %U http://architexte.ircam.fr/textes/Obin15a/

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