Paper: Predicting Intonational Phrasing From Text

ACL ID P91-1037
Title Predicting Intonational Phrasing From Text
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1991

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.