Prosody contains information that is lost when utterances are transcribed into letters or characters. This paper is concerned with exploiting such information for syntactic analysis of read Japanese sentences. In our previous work, we employed 12 prosodic features, and made a statistical model to represent the relationship between those features and dependency distances. Then, by incorporating the model in our parser, which allows the use of numerical information as linguistic knowledge, we showed that prosodic information is in fact effective for syntactic analysis. In the present work, we took up 24 prosodic features, and conducted an extensive search for effective ones. Also the statistical model was modified to account for the actual distribution of the feature values. In open experiments using an ATR 503-sentence database, parsing accuracy was improved by 21.2
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