Abstract

Prosodic phrasing is an important component in modern TTS systems, which inserts natural and reasonable breaks into long utterance. This paper reports the study of prosodic phrasing in unrestricted Chinese text. A text corpus of 500 sentences is collected from our speech database and manually labeled with syntactic structure and prosodic structure. Features and target prosody labels are extracted from the corpus and used as training examples for a rule-learning program. The acquired rules are evaluated on unseen sentences. The experiments show that the tree-level syntactic features are the most effective ones for Chinese prosodic phrasing. And chunk-level features can also help to improve the prediction accuracy.

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