Automatic generation of prosodic rules for speech synthesis

The paper describes automatic generation of speech synthesis rules which predict the accent component value (stress level) for the bunsetsu in long noun phrases. The rules are inductively inferred from a lot of speech data by using two kinds of tree-based methods, the conventional tree generation and the SBR-tree algorithm. The rule sets automatically generated by the two methods have the almost same performance and decrease the prediction error to about 14 Hz from 23 Hz of the accent component value. The rate of the correct reproduction of the change, that is increase or decrease, for adjacent bunsetsu pairs is also used as a measure of evaluation and the generated rule sets correctly reproduce about 80% of the change. Effectiveness of the rule sets is verified through a listening test. SBR-tree methods generate very compact rules which are easy for human experts to interpret and match with the former studies