Peer-Reviewed Journal Details
Mandatory Fields
Castilho, S., Moorkens, J., Gaspari, F., Calixto, I., Tinsley, J., Way, A.
2017
June
PRAGUE BULLETIN OF MATHEMATICAL LINGUISTICS
Is Neural Machine Translation the New State-of-the-Art?
Published
()
Optional Fields
108
109
120
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.
Prague, CZ
0032-6585
Print
https://ufal.mff.cuni.cz/pbml
Grant Details
Science Foundation Ireland (SFI)
The ADAPT Centre for Digital Content Technology at Dublin City University is funded under the Science Foundation Ireland Research Centres Programme (Grant 13/RC/ 2106) and is co-funded under the European Regional Development Fund.