Reordering Constraint Based on Document-Level Context

Takashi Onishi, Masao Utiyama, Eiichiro Sumita

Abstract: One problem with phrase-based statistical machine translation is the problem of longdistance reordering when translating between languages with different word orders, such as Japanese-English. In this paper, we propose a method of imposing reordering constraints using document-level context. As the document-level context, we use noun phrases which significantly occur in context documents containing source sentences. Given a source sentence, zones which cover the noun phrases are used as reordering constraints. Then, in decoding, reorderings which violate the zones are restricted. Experiment results for patent translation tasks show a significant improvement of 1.20% BLEU points in Japanese-English translation and 1.41% BLEU points in English-Japanese translation.