This paper deals with the problem of exploiting prosodic information in syntactic analysis of spontaneous monologue utterances of non-professional speakers. Duration of pauses at phrase boundaries and relative F0 contour features, which improve parsing accuracy of read sentences, were also found to be effective for parsing spontaneous speech. Dependency analysis was performed by the minimum penalty parser on academic presentation speech recorded in Corpus of Spontaneous Japanese, a large-scale database of spontaneous Japanese with rich linguistic annotations. Preliminary experiments on relatively clean parts of the monologue data utterances showed that the pause and F0 features are effective to improve the accuracy of dependency analysis of spontaneous utterances, and that combined use of both features will give further improvement. It was also found that the effectiveness of pause information was larger when pause models were estimated separately for zeroduration and non-zero-duration pauses, which better model the actual distribution of pause duration than a simple Gaussian distribution. Although this is a preliminary study, the results are promising.