Pitch Accent in Context: Predicting Intonational Prominence from Text (1995)
| Venue: | Artificial Intelligence |
| Citations: | 76 - 4 self |
BibTeX
@ARTICLE{Hirschberg95pitchaccent,
author = {Julia Hirschberg},
title = {Pitch Accent in Context: Predicting Intonational Prominence from Text},
journal = {Artificial Intelligence},
year = {1995},
volume = {63},
pages = {305--340}
}
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Abstract
Explaining speakers' choice of which items to emphasize or de-emphasize intonationally has been an important topic in theoretical linguistics, as well as in applications such as speech synthesis, where accent decisions affect the naturalness as well as interpretation. Heretofore, most researchers have assumed that detailed syntactic, semantic, and discourse-level information must be available in order for accent assignment to be predicted successfully. However, a series of recent experiments on corpora of recorded (read) speech and spontaneous (elicited) speech suggest that it is indeed possible to model human accent strategies with fair success (80-98% correct) for unrestricted text --- with only the tools for automatic text analysis currently available. The algorithm developed from these experiments is currently used to assign pitch accent in the Bell Laboratories Text-to-Speech System.
