Recursive Neural Network Based Preordering for English-to-Japanese Machine Translation

Yuki Kawara, Chenhui Chu, Yuki Arase

The word order between source and target languages significantly influences the translation quality. Preordering can effectively address this problem. Previous preordering methods require a manual feature design, making language dependent design difficult. In this paper, we propose a preordering method with recursive neural networks that learn features from raw inputs. Experiments show the proposed method is comparable to the state-of-the-art method but without a manual feature design.