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

arXiv: https://arxiv.org/abs/1805.10187 · HTML: https://mlsanity.com/paper/1805.10187/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 May 2018.

## Built on by (most cited first, 3 of 3)

- [Cross-Lingual Ability of Multilingual Masked Language Models: A Study of Language Structure](https://mlsanity.com/paper/2203.08430/) (2022)
- [Tree-constrained Pointer Generator with Graph Neural Network Encodings for Contextual Speech Recognition](https://mlsanity.com/paper/2207.00857/) (2022)
- [Graph Neural Networks for Contextual ASR with the Tree-Constrained Pointer Generator](https://mlsanity.com/paper/2305.18824/) (2023)

## Abstract (arXiv)

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