Research on predicting prosodic parameters for Chinese synthesis by data mining approach

Prosodic control is an important part of speech synthesis system. Prosodic parameters choice right or wrong influences the quality of synthetic speech directly. At present, text to speech system has less effective describe to reflect data relationships in the corpus. In this paper, we present a new research approach-data mining technology to discover those relationships by association rules modeling. We develop a new algorithm for generating association rules of prosodic parameters including pitch parameters and duration parameters from corpus. The output rules improve the correctness of syllable choice in text to speech system.