relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3870/
title: Adapting Neural Machine Translation for English-Vietnamese using Google Translate system for Back-translation
creator: Pham, Nghia Luan
creator: Nguyen, Van Vinh
subject: Information Technology (IT)
description: In this paper, we propose a method to better  leveraging monolingual data by exploiting the  advantages of GNMT system. Our method  for adapting a general neural machine translation  system to a specific domain, by exploiting  Back-translation technique using targetside  monolingual data. This solution requires  no changes to the model architecture from a  standard NMT system. Experiment results  show that our method can improve translation  quality, results significantly outperforming  strong baseline systems, our method improves  translation quality in legal domain up  to 13.65 BLEU points over the baseline system  for English-Vietnamese pair language.
date: 2019
type: Conference or Workshop Item
type: PeerReviewed
format: application/pdf
language: en
identifier: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3870/1/PACLIC%202019%20-%20Camera_ready.pdf
identifier:   Pham, Nghia Luan and Nguyen, Van Vinh  (2019) Adapting Neural Machine Translation for English-Vietnamese using Google Translate system for Back-translation.  In: Paclic 2019.