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2018
Conference Paper
Titel

Findings of the WMT 2018 Biomedical Translation Shared Task

Titel Supplements
Evaluation on Medline test sets
Abstract
Machine translation enables the automatic translation of textual documents between languages and can facilitate access to information only available in a given language for non-speakers of this language, e.g. research results presented in scientific publications. In this paper, we provide an overview of the Biomedical Translation shared task in the Workshop on Machine Translation (WMT) 2018, which specifically examined the performance of machine translation systems for biomedical texts. This year, we provided test sets of scientific publications from two sources (EDP and Medline) and for six language pairs (English with each of Chinese, French, German, Portuguese, Romanian and Spanish). We describe the development of the various test sets, the submissions that we received and the evaluations that we carried out. We obtained a total of 39 runs from six teams and some of this year's BLEU scores were somewhat higher that last year's, especially for teams that made use of biomedical resources or state-of-the-art MTalgorithms (e.g. Transformer). Finally, our manual evaluation scored automatic translations higher than the reference translations for German and Spanish.
Author(s)
Neves, Mariana
German Federal Institute for Risk Assessment (BfR)
Yepes, Antonio Jimeno
IBM Research, Australia
Névéol, Aurélie
LIMSI, CNRS, Uni. Paris Saclay, France
Grozea, Cristian
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS
Siu, Amy
Beuth University of Applied Sciences, Germany
Kittner, Madeleine
Humboldt-Universität zu Berlin, Germany
Verspoor, Karin
University of Melbourne, Australia
Hauptwerk
WMT 2018, Third Conference on Machine Translation. Proceedings of the conference
Konferenz
Conference on Machine Translation (WMT) 2018
Conference on Empirical Methods in Natural Language Processing (EMNLP) 2018
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