An Efficient Approach to Rule Redundancy Reduction in Hierarchical Phrase-Based Translation

摘要：

Hierarchical phrase-based machine translation model is a popular syntax model that makes use of the expressive power of Synchronous Context-Free Grammars (SCFG) to address the reordering problem in statistical machine translation. The model, however, generally suffers from a great amount of redundancy in the extracted translation rules. In this paper, we re-introduce the concept of rift into the rule extraction procedure to force the rules with reordering power to concentrate on where reordering has actually happened. Our approach brings a dramatic reduction in the training time and the number of the rules, with only minor sacrifice in translation quality.

关键词： Statistical machine translation hierarchical phrase redundancy rift

作者: Licheng FANG Chengqing ZONG

作者单位: Institute of Automation,CAS Beijing,China

会议类型: 国际会议

会议名称: The 2008 IEEE International Conference on Natural Language Processing and Knowledge Engineering(IEEE NLP-KE 2008)(2008IEEE自然语言处理与知识工程国际会议)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-19（万方平台首次上网日期，不代表论文的发表时间）