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<Paper uid="P05-1066">
  <Title>Clause Restructuring for Statistical Machine Translation</Title>
  <Section position="9" start_page="537" end_page="537" type="concl">
    <SectionTitle>
5 Conclusions
</SectionTitle>
    <Paragraph position="0"> We have demonstrated that adding knowledge about syntactic structure can significantly improve the performance of an existing state-of-the-art statistical machine translation system. Our approach makes use of syntactic knowledge to overcome a weakness of tradition SMT systems, namely long-distance reordering. We pose clause restructuring as a problem for machine translation. Our current approach is based on hand-crafted rules, which are based on our linguistic knowledge of how German and English syntax differs. In the future we may investigate data-driven approaches, in an effort to learn reordering models automatically. While our experiments are on German, other languages have word orders that are very different from English, so we believe our methods will be generally applicable.</Paragraph>
  </Section>
class="xml-element"></Paper>