Abstract
Prosodic patterns can be an important source of information for interpreting an utterance, but because the suprasegmental nature poses a challenge to computational modelling, prosody has seen limited use in automatic speech understanding. This work describes a new computational model of prosody aimed at recognizing detailed intonation patterns, both pitch accent and phrase boundary location and their specific tonal markers, using a multi-level representation to capture acoustic feature dependence at different time scales. The model assumes that an utterance is a sequence of phrases, each of which is composed of a sequence of syllable-level tone labels, which are in turn realized as a sequence of acoustic feature vectors (fundamental frequency and energy) depending in part on the segmental composition of the syllable. The variable lengths are explicitly modelled in a probabilistic representation of the complete sequence, using a dynamical system model at the syllable level that builds on existing models of intonation. Recognition and training algorithms are described, and initial experimental results are reported for prosodic labelling of radio news speech.
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Ostendorf, M., Ross, K. (1997). A Multi-level Model for Recognition of Intonation Labels. In: Sagisaka, Y., Campbell, N., Higuchi, N. (eds) Computing Prosody. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2258-3_19
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DOI: https://doi.org/10.1007/978-1-4612-2258-3_19
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