汉英机器翻译中的冠词处理研究

Research on Article Selection in Chinese English Machine Translation

对于汉英机器翻译而言，由于汉语中缺乏与英语冠词相应的语言范畴，而且面向人的冠词用法规则很难满足机器翻译处理的需要，冠词的误用严重地影响了最终译文的质量。本文提出一种将基于转换的错误驱动的学习机制用于冠词处理的策略，初步实验显示，这种方法可以有效地提高机器译文中冠词使用的准确率。

Because Chinese language has no corresponding category with English articles and the usage rules of articles oriented to human are difficult to operationalize for machine translation,there are many cases in using articles incorrectly in Chinese English machine translation system,which degrade the quality of the output translation severely.In this paper,we proposal a strategy for article selection which based the Transformation Based Error Driven Learning Algorithm,an initial experimental result shows the strategy can improve the accuracy in using articles.