We are still in the process of releasing our neural machine translation (NMT) code, which alleviates the problem of fluent but inadequate translations that NMT suffers.
Please refer to an improved NMT, which incorporates context gates to obtain a further improvement of 1.6 BLEU over NMT-Coverage.
In this version, we introduce a coverage mechanism (NMT-Coverage) to indicate whether a source word is translated or not, which proves to alleviate over-translation and under-translation. If you use the code, please cite our paper:
@InProceedings{Tu:2016:ACL,
author = {Tu, Zhaopeng and Lu, Zhengdong and Liu, Yang and Liu, Xiaohua and Li, Hang},
title = {Modeling Coverage for Neural Machine Translation},
booktitle = {Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics},
year = {2016},
}
For any comments or questions, please email the first author.
NMT-Coverage is developed by Zhaopeng Tu, which is on top of lisa-groudhog (https://github.com/lisa-groundhog/GroundHog). It requires Theano0.8 or above version (for the module "scan" used in the trainer).
To install NMT-Coverage in a multi-user setting
python setup.py develop --user
For general installation, simply use
python setup.py develop
NOTE: This will install the development version of Theano, if Theano is not currently installed.
See experiments/nmt/README.md