Statistical rhythmic metrics are applied on a Buckeye corpus of spontaneous interview speech in order to investigate the extent of inter-speaker rhythm variability. Tests are made on speech produced by speakers who share the same regional dialect in North America. The choice is made due to the unique characteristic of the Buckeye corpus in that the speech dataset is obtained from the speakers who have been raised in the same region and hence who share the same dialect with each other. Statistical measures of rhythm metrics are obtained from the subset of the corpus. The results of clustering analysis show that the rhythmic measures that capture the least dialectal variance is the normalized pair-wise variability indices calculated based on the respective adjacent consonantal and vocalic durations. The finding implies that these statistical measures of rhythm can be used in capturing the dialectal similarities on spontaneous speech.