M. Ostendorf,
``Prosodic Boundary Detection,''
in Prosody: Theory and Experiment. Studies Presented to Gosta Bruce, M. Horne (Ed.), Kluwer, forthcoming.

The perceived grouping of words in speech, i.e.\ prosodic constituent structure, contributes meaning to the sequence of words that comprise an utterance by highlighting its information structure. Since prosodic boundaries are known to be useful in human speech communication, it is natural to expect phrasing to be useful in computer speech understanding. This chapter addresses the problem of recognizing symbolic phrase boundaries given a speech signal, surveying a variety of proposed algorithms and their applications. In general, a phrase boundary model represents the mapping from text (generally syntactic structure) to the acoustic correlates that mark prosodic phrase structure (pauses, boundary tones, duration lengthening, etc.). However, the specifics of the model depend on the linguistic theory of phrasing, the mathematical framework of the model and the application of phrase boundary detection, as shown in a discussion of options for phrase detection. Three applications of prosodic phrase recognition are described here -- prosodic labeling, constraining speech/language processing search procedures, and prosodic scoring of word hypotheses -- together with their implications for algorithmic choices in phrase detection. The chapter concludes with a discussion of open problems in prosodic phrase recognition.

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