Feature rich translation model for example-based machine translation

Authors:
Yin Chen;Muyun Yang;Sheng Li;Hongfei Jiang
Affiliations:
Harbin Institute of Technology, MOE-MS Key Laboratory of Natural Language Processing and Speech, NanGang, Harbin, China;Harbin Institute of Technology, MOE-MS Key Laboratory of Natural Language Processing and Speech, NanGang, Harbin, China;Harbin Institute of Technology, MOE-MS Key Laboratory of Natural Language Processing and Speech, NanGang, Harbin, China;Harbin Institute of Technology, MOE-MS Key Laboratory of Natural Language Processing and Speech, NanGang, Harbin, China
Venue:
ICCPOL'06 Proceedings of the 21st international conference on Computer Processing of Oriental Languages: beyond the orient: the research challenges ahead
Year:
2006

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Abstract

Most EBMT systems select the best example scored by the similarity between the input sentence and existing examples. However, there is still much matching and mutual-translation information unexplored from examples. This paper introduces log-linear translation model into EBMT in order to adequately incorporate different kinds of features inherited in the translation examples. Instead of designing translation model by human intuition, this paper formally constructs a multi-dimensional feature space to include various features of different aspects. In the experiments, the proposed model shows significantly better result.