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Learning labelled dependencies in machine translation evaluation

He, Yifan and Way, Andy (2009) Learning labelled dependencies in machine translation evaluation. In: EAMT 2009 - 13th Annual Conference of the European Association for Machine Translation, 13-15 May 2009, Barcelona, Spain.

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Recently novel MT evaluation metrics have been presented which go beyond pure string matching, and which correlate better than other existing metrics with human judgements. Other research in this area has presented machine learning methods which learn directly from human judgements. In this paper, we present a novel combination of dependency- and machine learning-based approaches to automatic MT evaluation, and demonstrate greater correlations with human judgement than the existing state-of-the-art methods. In addition, we examine the extent to which our novel method can be generalised across different tasks and domains.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:machine translation evaluation;
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Next Generation Localisation (CNGL)
Research Initiatives and Centres > National Centre for Language Technology (NCLT)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in:Proceedings of the 13th Annual Conference of the EAMT. . European Association for Machine Translation.
Publisher:European Association for Machine Translation
Official URL:
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland, SFI 07/CE/I1142
ID Code:15159
Deposited On:15 Feb 2010 11:34 by DORAS Administrator. Last Modified 27 Apr 2010 11:29

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