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. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Kim, B., & Lee, G. G. (2006). C-TOBI-based pitch accent prediction using maximum-entropy model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3982 LNCS, pp. 21–30). Springer Verlag. https://doi.org/10.1007/11751595_3
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