本文通过对汉蒙机器翻译方法的研究,给出了一种基于实例的汉蒙机器翻译方法,并加以了实现。本文给出了用于汉蒙EBMT机器翻译的实例搜索以及短语片段划分、匹配、组合的方法。本文给出的方法是基于词语对齐的,利用词语对齐进行词语的匹配,并根据匹配词数和长度计算相似度,选取最好的实例。通过对齐信息,确定片段组合的策略,生成翻译结果。通过对方法的实现和实验,完成了一个基于实例的汉蒙机器翻译系统。
Abstract
We have presented an example based Chinese-Mongolian machine translation method, and implemented it. The method is insist of several parts, includes example searching, segment splitting, matching and recombining. The method is based on word alignment. It is using word alignment information for segment matching, and computing the similarity by the number of matching words and length, and selects the best example. Using word alignment information, determined the method of segment recombining, and generates the translation result.
关键词
人工智能 /
机器翻译 /
蒙古语 /
基于实例 /
词语对齐
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Key words
artificial intelligence /
machine translation /
mongolian /
example based /
word alignment
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参考文献
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脚注
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基金
国家自然基金资助项目(60573188);国家863计划资助项目(2003AA115510)
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