统计机器翻译中一致性解码方法比较分析

该文对近年来统计机器翻译研究中出现的多种一致性解码方法进行比较与分析。根据现有一致性解码方法对(单个或多个)统计机器翻译系统输出结果使用方式的不同,首先将其归纳为两大类 基于翻译假设重排序的一致性解码方法和基于翻译假设重组合的一致性解码方法;然后,针对每类方法,分别回顾其最具代表性的研究工作;最后,通过在大规模中—英机器翻译评测数据上的对比实验,对该文中介绍的多种方法进行比较,并对该课题未来研究方向进行展望。

A Comparative Analysis of Consensus Decoding Methods for Statistical Machine Translation

This paper presents a comparative analysis of various consensus decoding methods appeared in recent years for statistical machine translation (SMT). Based on different ways of using translation hypotheses generated by single or multiple SMT systems, we classify current consensus decoding methods into two categorieshypothesis reranking-based consensus decoding and hypothesis reconstruction-based consensus decoding. After reviewing the most representative work for each category, we perform Chinese-to-English machine translation experiments on large scale data sets to compare different methods listed in this paper. The future development prospects of consensus decoding is discussed as well.
Key wordsnatural language processing; statistical machine translation; consensus decoding; minimum Bayes-risk decoding; system combination