Title: Tree-Based Approaches to Automatic Generation of
Speech Synthesis Rules for Prosodic Parameters
Author: Yoichi Yamashita, Manabu Tanaka, Yoshitake Amako, Yasuo Nomura, Yoshikazu Ohta, Atsunori Kitoh, Osamu Kakusho and Riichiro Mizoguchi
Reference: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol.E76-A, No.11, pp.1934-1941.
This paper describes automatic generation of speech synthesis rules
which predict a stress level for each 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 decision tree and
the SBR-tree methods.
The rule sets automatically generated by two methods
have almost the same performance
and decrease the prediction error to about 14Hz from 23Hz
of the accent component value.
The rate of the correct reproduction of the change for adjacent
bunsetsu pairs is also used as a measure for evaluating the
generated rule sets
and they correctly reproduce the change of about 80%.
The effectiveness of the rule sets is verified through the listening test.
And, with regard to the comprehensiveness of the generated rules,
the rules by the SBR-tree methods are very compact and easy to human experts
to interpret and matches the former studies.
Keywords: speech synthesis, decision tree, automatic rule generation, accent component, long noun phrase