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Parser accuracy in quality estimation of machine translation: a tree kernel approach

Kaljahi, Rasoul Samed Zadeh, Foster, Jennifer orcid logoORCID: 0000-0002-7789-4853, Rubino, Raphael, Roturier, Johann and Hollowood, Fred (2013) Parser accuracy in quality estimation of machine translation: a tree kernel approach. In: International Joint Conference on Natural Language Processing (IJCNLP), 14-18 Oct 2013, Nagoya, Japan.

Abstract
We report on experiments designed to investigate the role of syntactic features in the task of quality estimation for machine translation, focusing on the effect of parser accuracy. Tree kernels are used to predict the segment-level BLEU score of English- French translations. In order to examine the effect of the accuracy of the parse tree on the accuracy of the quality estimation system, we experiment with various pars- ing systems which differ substantially with respect to their Parseval f-scores. We find that it makes very little difference which system we choose to use in the quality estimation task – this effect is particularly apparent for source-side English parse trees.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Parser accuracy
Subjects:Computer Science > Computational linguistics
Computer Science > Machine translating
Computer Science > Machine learning
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in: Proceedings of International Joint Conference on Natural Language Processing (IJCNLP). .
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:19961
Deposited On:26 May 2014 13:03 by Jennifer Foster . Last Modified 10 Oct 2018 14:43
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