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Tree Kernels for Machine Translation Quality Estimation
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology. (Datorlingvistik)
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology. (computational linguistics)
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology. (Datorlingvistik)
2012 (English)In: Proceedings of the 7th Workshop on Statistical Machine Translation, Association for Computational Linguistics, 2012, 109-113 p.Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

This paper describes Uppsala University’s submissions to the Quality Estimation (QE) shared task at WMT 2012. We present a QE system based on Support Vector Machine regression, using a number of explicitly defined features extracted from the Machine Translation input, output and models in combination with tree kernels over constituency and dependency parse trees for the input and output sentences. We confirm earlier results suggesting that tree kernels can be a useful tool for QE system construction especially in the early stages of system design.

Place, publisher, year, edition, pages
Association for Computational Linguistics, 2012. 109-113 p.
National Category
Language Technology (Computational Linguistics)
Research subject
Computational Linguistics
Identifiers
URN: urn:nbn:se:uu:diva-191418ISBN: 978-1-937284-20-6 (print)ISBN: 1-937284-20-4 (print)OAI: oai:DiVA.org:uu-191418DiVA: diva2:585636
Conference
Seventh Workshop on Statistical Machine Translation, Montréal, Canada, June 7–8, 2012
Available from: 2013-01-10 Created: 2013-01-10 Last updated: 2013-09-27Bibliographically approved

Open Access in DiVA

fulltext(455 kB)69 downloads
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Hardmeier, ChristianNivre, JoakimTiedemann, Jörg

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Output format
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