Castilho, Sheila ORCID: 0000-0002-8416-6555, Moorkens, Joss ORCID: 0000-0003-0766-0071, Gaspari, Federico ORCID: 0000-0003-3808-8418, Calixto, Iacer, Tinsley, John and Way, Andy ORCID: 0000-0001-5736-5930 (2017) Is neural machine translation the new state of the art? The Prague Bulletin of Mathematical Linguistics (108). ISSN 0032-6585
Abstract
This paper discusses neural machine translation (NMT), a new paradigm in the MT field,
comparing the quality of NMT systems with statistical MT by describing three studies using
automatic and human evaluation methods. Automatic evaluation results presented for NMT
are very promising, however human evaluations show mixed results. We report increases in
fluency but inconsistent results for adequacy and post-editing effort. NMT undoubtedly represents a step forward for the MT field, but one that the community should be careful not to
oversell.
Metadata
Item Type: | Article (Published) |
---|---|
Refereed: | Yes |
Subjects: | Computer Science > Machine translating |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing Research Initiatives and Centres > ADAPT |
Publisher: | PBML |
Official URL: | https://doi.org/10.1515/pralin-2017-0013 |
Copyright Information: | © 2017 PBML. Distributed under CC BY-NC-ND. |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
Funders: | TraMOOC project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement № 644333, e Science Foundation Ireland Research Centres Programme (Grant 13/RC/ 2106) and is co-funded under the European Regional Development Fund |
ID Code: | 23072 |
Deposited On: | 11 Mar 2019 12:53 by Thomas Murtagh . Last Modified 20 Jan 2021 16:52 |
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