Incorporating Linguistic Rules in Statistical Chinese Language Model for Pinyin-to-character Conversion

刘秉权; Wang; Xiaolong; Wang; Yuying

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Incorporating Linguistic Rules in Statistical Chinese Language Model for Pinyin-to-character Conversion

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摘要

An N-gram Chinese language model incorporating linguistic rules is presented. By constructing elements lattice, rules information is incorporated in statistical frame. To facilitate the hybrid modeling, novel methods such as MI-based rule evaluating, weighted rule quantification and element-based n-gram probability approximation are presented. Dynamic Viterbi algorithm is adopted to search the best path in lattice. To strengthen the model, transformation-based error-driven rules learning is adopted. Applying proposed model to Chinese Pinyin-to-character conversion, high performance has been achieved in accuracy, flexibility and robustness simultaneously. Tests show correct rate achieves 94.81% instead of 90.53% using bi-gram Markov model alone. Many long-distance dependency and recursion in language can be processed effectively.

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《高技术通讯：英文版》 |2001年第2期|8-13|共6页
作者
刘秉权; Wang; Xiaolong; Wang; Yuying;
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作者单位

Department of Computer Science and Engineering;

Harbin Institute of Technology;

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原文格式 PDF
正文语种 chi
中图分类信息处理（信息加工）;
关键词
Chinese Pinyin-to-character conversion; Rule-based language model; N-gram language model; Hybrid language model; Element lattice; Transformation-based error-driven learning;

Incorporating Linguistic Rules in Statistical Chinese Language Model for Pinyin-to-character Conversion

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