Type

Journal Article

Authors

Andy Way
John Tinsley
Iacer Calixto
Federico Gaspari
Joss Moorkens
Sheila Castilho

Subjects

Linguistics

Topics
evaluation methods state of the art machine translating statistical mt machine translation post editing effort community human

Is neural machine translation the new state of the art? (2017)

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.
Collections Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing: School of Computing
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: ADAPT
Ireland -> Dublin City University -> Publication Type = Article
Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> Subject = Computer Science: Machine translating

Full list of authors on original publication

Andy Way, John Tinsley, Iacer Calixto, Federico Gaspari, Joss Moorkens, Sheila Castilho

Experts in our system

1
Andy Way
Dublin City University
Total Publications: 229
 
2
John Tinsley
Dublin City University
Total Publications: 13
 
3
Iacer Calixto
Dublin City University
Total Publications: 6
 
4
Federico Gaspari
Dublin City University
Total Publications: 9
 
5
Joss Moorkens
Dublin City University
Total Publications: 17
 
6
Sheila Castilho
Dublin City University
Total Publications: 16