首页> 外文会议>International conference on computational linguistics;COLING-96 >Bilingual Knowledge Acquisition from Korean-English Parallel Corpus Using Alignment Method ( Korean-English Alignment at Word and Phrase Level )
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Bilingual Knowledge Acquisition from Korean-English Parallel Corpus Using Alignment Method ( Korean-English Alignment at Word and Phrase Level )

机译:使用对齐方式从韩英平行语料库中获取双语知识(单词和短语级别的韩英对齐)

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This paper suggests a method to align Korean-English parallel corpus. The structural dissimilarity between Korean and Indo-European languages requires more flexible measures to evaluate the alignment candidates between the bilingual units than is used to handle the pairs of Indo-European languages. The flexible measure is intended to capture the dependency between bilingual items that can occur in different units according to different ordering rules. The proposed method to accomplish Korean-English alignment takes phrases as an alignment unit that is a departure from the existing methods taking words as the unit. Phrasal alignment avoids the problem of alignment units and appease the problem of ordering mismatch. The parameters are estimated using the EM algorithm. The proposed alignment algorithm is based on dynamic programming. In the experiments carried out on 253,000 English words and its Korean translations the proposed method achived 68.7% in accuracy at phrase level and 89.2% in accuracy with the bilingual dictionary induced from the alignment. The result of the alignment may lead to richer bilingual data than can be derived from only word-level aligments.
机译:本文提出了一种对齐韩英平行语料库的方法。与用于处理印欧语对时相比,韩语和印欧语之间的结构差异要求更灵活的措施来评估双语单位之间的对齐候选。灵活的措施旨在捕获双语项目之间的依赖关系,这些双语项目可能会根据不同的排序规则以不同的单位出现。所提出的实现韩语-英语对齐的方法将短语作为对齐单位,这与以单词为单位的现有方法有所不同。短语对齐避免了对齐单元的问题,并缓解了排序不匹配的问题。使用EM算法估计参数。提出的对齐算法基于动态规划。在对253,000个英语单词及其韩语翻译进行的实验中,所提出的方法在短语级别上的准确度达到了68.7%,而通过对齐生成的双语词典则达到了89.2%的准确性。对齐的结果可能会导致比仅从单词级匹配项获得的双语数据更丰富。

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