An Improved Graph Model for Chinese Spell Checking
Yang Xin, Hai Zhao, Yuzhu Wang, Zhongye Jia · 2014
In this paper, we propose an improved graph model for Chinese spell checking.The model is based on a graph model for generic errors and two independentlytrained models for specific errors.First, a graph model represents a Chinese sentence and a modified single source shortest path algorithm is performed on the graph to detect and correct generic spelling errors.Then, we utilize conditional random fields to solve two specific kinds of common errors: the confusion of "在" (at) (pinyin is 'zai' in Chinese), "再" (again, more, then) (pinyin: zai) and "的" (of) (pinyin: de), "地" (-ly, adverb-forming particle) (pinyin: de), "得" (so that, have to) (pinyin: de).Finally, a rule based system is exploited to solve the pronoun usage confusions: "她" (she) (pinyin: ta), "他" (he) (pinyin: ta) and some others fixed collocation errors.The proposed model is evaluated on the standard data set released by the SIGHAN Bake-off 2014 shared task, and gives competitive result.