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Erschienen in:
2006 | OriginalPaper | Buchkapitel
C-TOBI-Based Pitch Accent Prediction Using Maximum-Entropy Model
verfasst von : Byeongchang Kim, Gary Geunbae Lee
Erschienen in: Computational Science and Its Applications - ICCSA 2006
Verlag: Springer Berlin Heidelberg
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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.