Mandarin Prosodic Phrase Prediction based on Syntactic Trees

Abstract

Prosodic phrases (PPs) are important for Mandarin Text-To-Speech systems. Most of the existing PP detection methods need large manually annotated corpora to learn the models. In this paper, we propose a rule based method to predict the PP boundaries employing the syntactic information of a sentence. The method is based on the ob-servation that a prosodic phrase is a meaningful segment of a sentence with length restrictions. A syntactic structure allows to segment a sentence according to grammars. We add some length restrictions to the segmentations to predict the PP boundaries. An F-Score of 0.693 was obtained in the experiments, which is about 0.02 higher than the one got by a Conditional Random Field based method.