Kyoto-NMT: a Neural Machine Translation implementation in Chainer

Fabien Cromières


Abstract
We present Kyoto-NMT, an open-source implementation of the Neural Machine Translation paradigm. This implementation is done in Python and Chainer, an easy-to-use Deep Learning Framework.
Anthology ID:
C16-2064
Volume:
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations
Month:
December
Year:
2016
Address:
Osaka, Japan
Editor:
Hideo Watanabe
Venue:
COLING
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
307–311
Language:
URL:
https://aclanthology.org/C16-2064
DOI:
Bibkey:
Cite (ACL):
Fabien Cromières. 2016. Kyoto-NMT: a Neural Machine Translation implementation in Chainer. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations, pages 307–311, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Kyoto-NMT: a Neural Machine Translation implementation in Chainer (Cromières, COLING 2016)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingest-bitext-workshop/C16-2064.pdf
Code
 fabiencro/knmt