Hierarchical Phrase-based Machine Translation with Word-based Reordering Model
Hierarchical Phrase-based Machine Translation with Word-based Reordering Model
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发表时间：
2010-08
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通讯作者：
K. Hayashi;Hajime Tsukada;Katsuhito Sudoh;Kevin Duh;Seiichi Yamamoto
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作者：
K. Hayashi;Hajime Tsukada;Katsuhito Sudoh;Kevin Duh;Seiichi Yamamoto
基于分层短语的机器翻译可以使用同步上下文无关语法捕获全局重新排序，但在解码过程中几乎无法评估单词排序的正确性。我们提出了一种将基于单词的重新排序模型集成到基于分层短语的机器翻译中的方法来克服这个弱点。我们的方法扩展了基于分层短语的模型的同步上下文无关语法规则，以包含重新排序的源字符串，从而允许在解码期间有效计算重新排序模型分数。我们在日语到英语的基本旅行表达语料库上的实验结果表明，我们提出的系统获得的 BLEU 分数优于标准的基于分层短语的机器翻译系统获得的分数。
Hierarchical phrase-based machine translation can capture global reordering with synchronous context-free grammar, but has little ability to evaluate the correctness of word orderings during decoding. We propose a method to integrate word-based reordering model into hierarchical phrase-based machine translation to overcome this weakness. Our approach extends the synchronous context-free grammar rules of hierarchical phrase-based model to include reordered source strings, allowing efficient calculation of reordering model scores during decoding. Our experimental results on Japanese-to-English basic travel expression corpus showed that the BLEU scores obtained by our proposed system were better than those obtained by a standard hierarchical phrase-based machine translation system.