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Maximising TM performance through sub-tree alignment and SMT

Zhechev, Ventsislav and van Genabith, Josef (2010) Maximising TM performance through sub-tree alignment and SMT. In: the Ninth Conference of the Association for Machine Translation in the Americas (AMTA 2010)., 31 Oct - 4 Nov 2010, Denver, Colorado.

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Abstract

With the steadily increasing demand for high quality translation, the localisation industry is constantly searching for technologies that would increase translator throughput, in particular focusing on the use of high-quality Statistical Machine Translation (SMT) supplementing the established Translation Memory (TM) technology. In this paper, we present a novel modular approach that utilises state-of-the-art sub-tree alignment and SMT techniques to turn the fuzzy matches from a TM into near perfect translations. Rather than relegate SMT to a last-resort status where it is only used should the TM system fail to produce the desired output, for us SMT is an integral part of the translation process that we rely on to obtain high-quality results. We show that the presented system consistently produces better quality output than the TM and performs on par or better than the standalone SMT system.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Statistical Machine Translation; SMT; Translation Memory; TM
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
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:16019
Deposited On:07 Jun 2011 14:38 by Shane Harper. Last Modified 07 Jun 2011 14:38

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