Prosodic Phrase Segmentation Based on Pitch-Pattern Clustering.

This paper proposes a method to detect the prosodic phrase for speaker-independent continuous speech. The method uses continuous adjustment of a pitch pattern with the learning accent pattern (pitch template). The accent phrase with one accent cue and its corresponding pitch pattern are considered correlated. Distinctive pitch templates are obtained by classifying the pitch patterns corresponding to the accent phrase with the help of clustering. Since pitch patterns of continuous speech are connected to these pitch templates, prosodic phrase segmentation can easily be done by One-Stage DP matching of the pitch pattern with pitch templates. The method can also be applied to unspecified speakers whose average pitch frequency differs from each other by sliding the pitch template along the vertical axis during the matching. The ATR continuous speech database (10 speakers, 503 sentences) is used for the experiments. For eight templates, about 65 percent of the automatic prosodic phrase segmentations were correct and the experiment was successful in detecting about 83 percent of the prosodic phrase boundaries. [ABSTRACT FROM AUTHOR]