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.
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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