Probabilistic parse scoring with prosodic information

Prosodic patterns provide important cues for resolving syntactic ambiguity, and can be used to improve the accuracy of automatic speech understanding. With this goal, the authors 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 achieve ambiguity resolution performance close to that of human listeners.<>