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一种基于改进隐马尔克夫模型的词语对齐方法 被引量:2

An Improved HMM Based Word Alignment Method
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摘要 该文在基本隐马尔克夫模型的基础之上,利用句法知识来改进词语对齐,把英语的短语结构树距离和基本隐马尔克夫模型相结合进行词语对齐。与基本隐马尔克夫模型相比,这个模型可以降低词语对齐的错误率,并且提高统计机器翻译系统BLEU值,从而提高机器翻译质量。 This paper improves the HMM based word alignment by introducing syntactic knowledge. HMM is com- bined with English phrase structure tree distance to align Chinese-English words. Experiments shows that the im- proved HMM ean reduce the error rate of word alignment, and improve the BLEU score of statistical machine trans- lation.
作者 刘颖 姜巍
机构地区 清华大学中文系
出处 《中文信息学报》 CSCD 北大核心 2014年第2期51-55,共5页 Journal of Chinese Information Processing
基金 教育部回国人员启动项目(20101021603)
关键词 短语结构树距离 隐马尔克夫模型 词语对齐 BLEU值 phrase structure tree distance hidden Markov model word alignment BLEU score
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参考文献13

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二级参考文献19

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