层次化短语翻译的导向模型

Xinyan Xiao, Jinsong Su, Yang Liu, Qun Liu, Shouxun Lin
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引用次数: 6

摘要

基于分层短语(HPB)的翻译利用语法的力量来执行长距离重排序,而不需要针对相邻块指定非终结符的方向,也不需要考虑非终结符所涵盖的词汇信息。在本文中,我们从基于短语的系统中借鉴了导向模型的思想来增强HPB翻译的重新排序能力。我们根据语法对齐区分非终结语的三种方向(单调、交换、不连续),并利用其所涵盖的词汇信息选择合适的非终结语方向。通过引入定向模型,我们的方法在大规模NIST汉英翻译任务上的性能显著优于标准HPB系统,在大规模NIST汉英翻译任务上的性能高达1.02 Bleu,在WMT德英翻译任务上的性能高达0.51 Bleu。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Orientation Model for Hierarchical Phrase-Based Translation
The hierarchical phrase-based (HPB) translation exploits the power of grammar to perform long distance reorderings, without specifying nonterminal orientations against adjacent blocks or considering the lexical information covered by nonterminals. In this paper, we borrow from phrase-based system the idea of orientation model to enhance the reordering ability of HPB translation. We distinguish three orientations (monotone, swap, discontinuous) of a nonterminal based on the alignment of grammar, and select the appropriate orientation of nonterminal using lexical information covered by it. By incorporating the orientation model, our approach significantly outperforms a standard HPB system up to 1.02 Bleu on large scale NIST Chinese-English translation task, and 0.51 Bleu on WMT German-English translation task.
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