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<Paper uid="N06-1032">
  <Title>Grammatical Machine Translation</Title>
  <Section position="8" start_page="254" end_page="254" type="concl">
    <SectionTitle>
7 Conclusion
</SectionTitle>
    <Paragraph position="0"> We presented an SMT model that marries phrase-based SMT with traditional grammar-based MT by incorporating a grammar-based generator into a dependency-based SMT system. Under the NIST measure, we achieve results in the range of the state-of-the-art phrase-based system of Koehn et al. (2003) for in-coverage examples of the LFG-based system. A manual evaluation of a large set of such examples shows that on in-coverage examples our system achieves significant improvements in grammaticality and also translational adequacy over the phrase-based system. Fortunately, it is determinable when our system is in-coverage, which opens the possibility for a hybrid system that achieves improved grammaticality at state-of-the-art translation quality. Future work thus will concentrate on improvements of in-coverage translations e.g., by stochastic generation. Furthermore, we intend to apply our system to other language pairs and larger data sets.</Paragraph>
  </Section>
class="xml-element"></Paper>