The relative size and location of prosodic phrase boundaries provides an important cue for resolving syntactic ambiguity, and can be used to improve the accuracy of automatic speech understanding. This paper describes an approach to scoring candidate sentence hypotheses and associated parses using prosodic phrase cues. Specifically, for each hypothesized parse, prosodic breaks are automatically detected and the probability of these breaks given the parse is computed based on a stochastic model of the prosody/syntax relationship. The parse probability can be used to rank sentence hypotheses and associated parses, optionally in combination with other scores. Both the prosodic break recognition algorithm and the prosody /syntax model can be automatically trained and can therefore be designed specifically for different speaking styles or task domains, given appropriate labeled data. We have demonstrated the potential of this approach in experiments with a corpus of ambiguous sentences spoken by FM radio announcers. Disambiguation performance is comparable to that of human listeners using the algorithm with hand-labeled breaks, although there is some performance degradation with the fully automatic system.
Cite as: Veilleux, N.M., Ostendorf, M., Wightman, C. (1992) Parse scoring with prosodic information. Proc. 2nd International Conference on Spoken Language Processing (ICSLP 1992), 1605-1608, doi: 10.21437/ICSLP.1992-399
@inproceedings{veilleux92_icslp,
author={N. M. Veilleux and Mari Ostendorf and Colin Wightman},
title={{Parse scoring with prosodic information}},
year=1992,
booktitle={Proc. 2nd International Conference on Spoken Language Processing (ICSLP 1992)},
pages={1605--1608},
doi={10.21437/ICSLP.1992-399},
issn={2958-1796}
}