利用依存限制抽取长距离调序规则

摘要

Long distance reordering is a key problem in statistical machine translation (SMT). Hierarchical phrasebased model offers an alternative to address this problem by using hierarchical rules that could characterize both local and long distance reordering. However, extracting long distance reordering rules with traditional algorithm will cuase heavy cost in decoder time-and-memory. We propose a new algorithm to extract long distance reordering rules with an extra dependency restriction. Our experiments show that our method achieves 0.74 point improvement in BLEU score.%长距离调序是统计机器翻译领域的一个重要问题.层次短语模型提供了一个很好的解决方案,它使用层次短语规则可以很好地表示局部调序和长距离调序.但是,使用传统的算法抽取长距离层次规则将会导致规则表数量急剧增加,从而加大解码内存和时间消耗.为了解决这个问题,该文提出了一种利用依存限制抽取长距离调序规则的新方法.实验表明,该文的方法可以比基准系统高出0.74个BLEU点.