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<Paper uid="H05-1009">
  <Title>Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP), pages 65-72, Vancouver, October 2005. c(c)2005 Association for Computational Linguistics NeurAlign: Combining Word Alignments Using Neural Networks</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> 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.</Paragraph>
  </Section>
class="xml-element"></Paper>