2006 AlignmentbyAgreement

• (Liang et al., 2006) ⇒ Percy Liang, Ben Taskar, and Dan Klein. (2006). “Alignment by Agreement.” In: Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics. doi:10.3115/1220835.1220849

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222006%22+Alignment+by+Agreement
• http://dl.acm.org/citation.cfm?id=1220835.1220849&preflayout=flat#citedby

Quotes

Abstract

We present an unsupervised approach to symmetric word alignment in which two simple asymmetric models are trained jointly to maximize a combination of data likelihood and agreement between the models. Compared to the standard practice of intersecting predictions of independently-trained models, joint training provides a 32% reduction in AER. Moreover, a simple and efficient pair of HMM aligners provides a 29% reduction in AER over symmetrized IBM model 4 predictions.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2006 AlignmentbyAgreement	Dan Klein Percy Liang Ben Taskar			Alignment by Agreement				10.3115/1220835.1220849		2006