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Example-based machine translation via the web

Gough, Nano, Way, Andy orcid logoORCID: 0000-0001-5736-5930 and Hearne, Mary (2002) Example-based machine translation via the web. In: AMTA 2002 - 5th Conference of the Association for Machine Translation in the Americas, 8-12 October 2002, Tiburon, CA, USA. ISBN 978-3-540-44282-0

Abstract
One of the limitations of translation memory systems is that the smallest translation units currently accessible are aligned sentential pairs. We propose an example-based machine translation system which uses a 'phrasal lexicon' in addition to the aligned sentences in its database. These phrases are extracted from the Penn Treebank using the Marker Hypothesis as a constraint on segmentation. They are then translated by three on-line machine translation (MT) systems, and a number of linguistic resources are automatically constructed which are used in the translation of new input. We perform two experiments on testsets of sentences and noun phrases to demonstrate the effectiveness of our system. In so doing, we obtain insights into the strengths and weaknesses of the selected on-line MT systems. Finally, like many example-based machine translation systems, our approach also suffers from the problem of ‘boundary friction’. Where the quality of resulting translations is compromised as a result, we use a novel, post hoc validation procedure via the World Wide Web to correct imperfect translations prior to their being output to the user.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Additional Information:The original article is available at www.springerlink.com
Uncontrolled Keywords:example-based machine translation;
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:Research Initiatives and Centres > National Centre for Language Technology (NCLT)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in: Machine Translation: From Research to Real Users. Lecture Notes in Computer Science 2499. Springer Berlin / Heidelberg. ISBN 978-3-540-44282-0
Publisher:Springer Berlin / Heidelberg
Official URL:http://dx.doi.org/10.1007/3-540-45820-4_8
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:15347
Deposited On:09 Apr 2010 10:59 by DORAS Administrator . Last Modified 16 Nov 2018 12:02
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