Predicting Intonational Phrasing From Text

PREDICTING INTONATIONAL PHRASING FROM TEXT Michelle Q. Wang Churchill College Cambridge University Cambridge UK Julia Hirschberg AT&T Bell Laboratories 600 Mountain Avenue Murray Hill, NJ 07974 Abstract Determining the relationship between the intona- tional characteristics of an utterance and other features inferable from its text is important both for speech recognition and for speech synthesis. This work investigates the use of text analysis in predicting the location of intonational phrase boundaries in natural speech, through analyzing 298 utterances from the DARPA Air Travel In- formation Service database. For statistical model- ing, we employ Classification and Regression Tree (CART) techniques. We achieve success rates of just over 90%, representing a major improvement over other attempts at boundary prediction from unrestricted text. 1 Introduction The relationship between the intonational phras- ing of an utterance and other features which can be inferred from its transcription represents an important source of information for speech syn- thesis and speech recognition. In synthesis, more natural intonational phrasing can be assigned if text analysis can predict human phrasing perfor- mance. In recognition, better calculation of prob- able word durations is possible if the phrase-final- lengthening that precedes boundary sites can be predicted. Furthermore, the association of intona- tional features with syntactic and acoustic infor- mation can also be used to reduce the number of sentence hypotheses under consideration. Previous research on the location of intonational boundaries has largely focussed on the relation- ship between these prosodic boundaries and syn- tactic constituent boundaries. While current re- search acknowledges the role that semantic and discourse-level information play in boundary as- I We thank Michael Riley for helpful discussions. Code implementing the CART techniques employed here was written by Michael Riley and Daryi Pregibon. Part-of- speech tagging employed Ken Church's tagger, and syn- tactic analysis used Don Hindle's parser, Fiddltch. signment, most authors assume that syntactic con- figuration provides the basis for prosodic 'defaults' that may be overridden by semantic or discourse considerations. While most interest in boundary prediction has been focussed on synthesis (Gee and Grosjean, 1983; Bachenko and Fitzpatrick, 1990), currently there is considerable interest in predicting boundaries to aid recognition (Osten- doff et al., 1990; Steedman, 1990). The most successful empirical studies in boundary location have investigated how phrasing can disambiguate potentially syntactically ambiguous utterances in read speech (Lehiste, 1973; Ostendorf et al., 1990). Analysis based on corpora of natural speech (Ab tenberg, 1987) have so far reported very limited success and have assumed the availability of syn- tactic, semantic, and discourse-level information well beyond the capabilities of current NL systems to provide. To address the question of how boundaries are assigned in natural speech -- as well as the need for classifying boundaries from information that can be extracted automatically from text -- we examined a multi-speaker corpus of spontaneous elicited speech. We wanted to compare perfor- mance in the prediction of intonational bound- aries from information available through simple techniques of text analysis, to performance us- ing information currently available only come from hand labeling …

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