Translation selection through machine learning with language resources

Authors:
Hyun Ah Lee
Affiliations:
School of Computer and Software Engineering, Kumoh National Institute of Technology, Gyeongbuk, Republic of Korea
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

Knowledge acquisition is a critical problem for machine translation and translation selection. In this paper, I propose a tranlsation selection method that combines variable features from multiple language resources using machine learning. I introduce multiple measures for sense disambiguation and word selection that are based on language resources, and apply machine learning to combine those measures for translation selection. In evaluation, precision of translation selection improves even though a small-sized bilingual corpus is used as training data.