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The Effect of Translationese on Tuning for Statistical Machine Translation
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.
2017 (English)In: Proceedings of the 21st Nordic Conference on Computational Linguistics, 2017, p. 241-246Conference paper, Published paper (Refereed)
Abstract [en]

We explore how the translation direction in the tuning set used for statistical machine translation affects the translation results. We explore this issue for three language pairs. While the results on different metrics are somewhat conflicting, using tuning data translated in the same direction as the translation systems tends to give the best length ratio and Meteor scores for all language pairs. This tendency is confirmed in a small human evaluation.

Place, publisher, year, edition, pages
2017. p. 241-246
National Category
Language Technology (Computational Linguistics)
Research subject
Computational Linguistics
Identifiers
URN: urn:nbn:se:uu:diva-338548OAI: oai:DiVA.org:uu-338548DiVA, id: diva2:1172490
Conference
The 21st Nordic Conference on Computational Linguistics
Available from: 2018-01-10 Created: 2018-01-10 Last updated: 2018-01-13Bibliographically approved

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fulltext(98 kB)4 downloads
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Stymne, Sara
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf