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NeurAlign: combining word alignments using neural networks

TitleNeurAlign: combining word alignments using neural networks
Publication TypeConference Paper
Year of Publication2005
AuthorsAyan N F, Dorr BJ, Monz C
Conference NameConference on Human Language Technology and Empirical Methods in Natural Language Processing
PublisherAssociation for Computational Linguistics
Conference LocationVancouver, British Columbia, Canada

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.