Rule-based Reordering Constraints for Phrase-based SMT

Translation results suffer when a standard phrase-based statistical machine transla-tion system is used for translating long sen-tences. The translation output will not pre-serve the same word order as the source, especially between a language pair that has different syntactic structures. When a sentence is long, it should be partitioned into several clauses, and the word reorder-ing during the translation should be done within clauses, not between clauses. In this paper, we propose splitting the long sentences using linguistic information, and translating the sentences with the split boundaries. In other words, we constrain the word reordering so that it cannot cross the boundaries. We propose two types of constraints: split condition and block con-dition. By doing so, word order can be pre-served and translation quality improved. Our experiments on the patent translation between Japanese and English are able to achieve better translations measured by BLEU score, NIST score and word error rate (WER).