@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} }