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Improving Machine Translation: The Gap Between Research Approaches and Industry Needs

Kimberley Harris; Aljoscha Burchardt
In: Jörg Porsiel (Hrsg.). Machine Translation. Chapter 8, ISBN 9783938430934, BDÜ Weiterbildungs- und Fachverlagsgesellschaft mbH, Berlin, 2017.

Abstract

Translation quality evaluation (QE) has gained significant uptake in recent years, in particular in light of increased demand for automated translation workflows and higher quality machine translation. Yet, despite the need for innovative and forward-looking quality evaluation solutions, the technology landscape remains highly fragmented, with the two major constituencies in need of collaborative and ground-breaking technology still very divided. Closer cooperation between users of QE technology in research and industry would greatly benefit efforts to improve the quality of machine translation results, most significantly in the area of quality estimation and evaluation.

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