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Exploiting source similarity for SMT using context-informed features

Stroppa, Nicolas and van den Bosch, Antal and Way, Andy (2007) Exploiting source similarity for SMT using context-informed features. In: TMI-07 - Proceedings of The 11th Conference on Theoretical and Methodological Issues in Machine Translation, 7-9 September 2007, Skövde, Sweden.

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In this paper, we introduce context informed features in a log-linear phrase-based SMT framework; these features enable us to exploit source similarity in addition to target similarity modeled by the language model. We present a memory-based classification framework that enables the estimation of these features while avoiding sparseness problems. We evaluate the performance of our approach on Italian-to-English and Chinese-to-English translation tasks using a state-of-the-art phrase-based SMT system, and report significant improvements for both BLEU and NIST scores when adding the context-informed features.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:statistical machine translation;
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:Research Initiatives and Centres > National Centre for Language Technology (NCLT)
Official URL:
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:15226
Deposited On:18 Feb 2010 13:30 by DORAS Administrator. Last Modified 27 Apr 2010 15:03

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