基于数据挖掘算法的汉语合成韵律参数预测方法
Research on predicting prosodic parameters for Chinese synthesis by data mining approach
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摘要: 韵律模块是语音合成系统中的重要组成部分,韵律特征参数的描述正确与否直接影响合成系统的输出,针对目前语音合成系统中缺乏对前后音节的韵律参数之间关系的有效描述,提出一种新的韵律参数预测方法——数据挖掘技术来发现音节韵律参数之间的相互关系,通过其中的关联规则模型对这些关系进行描述,并基于关联发现算法获得汉语韵律参数中基频参数和时长参数的变化规则,研究表明这些规则可以较好地为多样本拼接合成系统的选音提供帮助和指导。Abstract: 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.