@conference {13835,
	title = {NeurAlign: combining word alignments using neural networks},
	booktitle = {Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing},
	series = {HLT {\textquoteright}05},
	year = {2005},
	month = {2005///},
	pages = {65 - 72},
	publisher = {Association for Computational Linguistics},
	organization = {Association for Computational Linguistics},
	address = {Stroudsburg, PA, USA},
	abstract = {This paper presents a novel approach to combining different word alignments. We view word alignment as a pattern classification problem, where alignment combination is treated as a classifier ensemble, and alignment links are adorned with linguistic features. A neural network model is used to learn word alignments from the individual alignment systems. We show that our alignment combination approach yields a significant 20--34\% relative error reduction over the best-known alignment combination technique on English-Spanish and English-Chinese data.},
	doi = {10.3115/1220575.1220584},
	url = {http://dx.doi.org/10.3115/1220575.1220584},
	author = {Ayan,Necip Fazil and Dorr, Bonnie J and Monz,Christof}
}
