基于浅层句法信息的翻译实例获取方法研究

Extraction of TrAnslation ExAmple Based on Shallow Parsing Information

翻译实例库是基于实例的机器翻译系统的主要知识源。本文采用基于浅层句法分析的方法进行翻译实例的获取。首先根据浅层句法信息划分源语言和目标语言的翻译单元,然后在词对齐结果的指导下,利用统计对齐模型确定源语言和目标语言翻译单元之间的映射关系,从而获取翻译实例。通过与几种较具代表性的翻译实例获取方法进行对比实验发现,无论是对翻译实例库直接评测,还是通过EBMT系统进行间接评测,该方法都获得了令人满意的效果。

Translation example base is the main knowledge source of example-based machine translation system. In this paper, a shallow parsing information based approach is proposed to extract translation examples. First, translation units of source and target language sentences are segmented respectively according to shallow parsing information. Then, guided by word alignment result, an statistical model is used to align translation units between source and target translation units, and thus translation examples are extracted. Experiment result shows that the proposed method achieves satisfying result in both direct evaluation of example base and indirect evaluation by EBMT system.