C-TOBI-Based pitch accent prediction using maximum-entropy model

Authors:
Byeongchang Kim;Gary Geunbae Lee
Affiliations:
School of Computer & Information Communications Engineering, Catholic University of Daegu, South Korea;Department of Computer Science & Engineering, Pohang University of Science & Technology, Pohang, South Korea
Venue:
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part III
Year:
2006

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Abstract

We model Chinese pitch accent prediction as a classification problem with six C-ToBI pitch accent types, and apply conditional Maximum Entropy (ME) classification to this problem. We acquire multiple levels of linguistic knowledge from natural language processing to make well-integrated features for ME framework. Five kinds of features were used to represent various linguistic constraints including phonetic features, POS tag features, phrase break features, position features, and length features.