Probabilistic parse scoring with prosodic information

Authors:
N. M. Veilleux;M. Ostendorf
Affiliations:
Electrical, Computer and Systems Engineering, Boston University, Boston, MA;Electrical, Computer and Systems Engineering, Boston University, Boston, MA
Venue:
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: speech processing - Volume II
Year:
1993

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Abstract

Prosodic patterns provide important cues for resolving syntactic ambiguity, and can be used to improve the accuracy of automatic speech understanding. With this goal, we propose a method of scoring syntactic parses in terms of observed prosodic cues, which can be used in ranking sentence hypotheses and associated parses. Specifically, the score is the probability of a hypothesized word sequence and associated syntactic parse given acoustic features, based on acoustic and "language" (prosody/syntax) models that represent probabilities in terms of abstract prosodic labels. Experimental results on a corpus of ambiguous sentence pairs indicate that the algorithm achieves disambiguation performance close to that of human listeners.