This paper reports the results of an indepth evaluation of 34 state-of-the-art domain-adapted machine translation (MT) systems that were built by four leading MT companies as part of the EU-funded iADAATPA project. These systems support a wide variety of languages for several domains. The evaluation combined automatic metrics and human methods, namely assessments of adequacy, fluency, and comparative ranking. The paper also discusses the most effective techniques to build domain-adapted MT systems for the relevant language combinations and domains.
Forcada, Mikel, Way, Andy, Tinsley, John, Shterionov, Dimitar, Rici, Celia and Gaspari, Federico, (eds.)
Proceedings of MT Summit XVII.
2.
European Association for Machine Translation.
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Funders:
INEA through grant N ◦ 2016-EU-IA-0132 as part of the EU’s CEF Telecom Programme, 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.
ID Code:
23863
Deposited On:
21 Oct 2019 12:30 by
Andrew Way
. Last Modified 20 Jan 2021 16:41