Utilizing Global Syntactic Tree Features for Phrase Reordering
Yeon-Soo Lee, Hyoung-Gyu Lee, Hae‐Chang Rim, Young-Sook Hwang · IEICE Transactions on Information and Systems · 2014
In phrase-based statistical machine translation, long distance reordering problem is one of the most challenging issues when translating syntactically distant language pairs. In this paper, we propose a novel reordering model to solve this problem. In our model, reordering is affected by the overall structures of sentences such as listings, reduplications, and modifications as well as the relationships of adjacent phrases. To this end, we reflect global syntactic contexts including the parts that are not yet translated during the decoding process.