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<Paper uid="C00-2163">
  <Title>A Comparison of Alignment Models for Statistical Machine Translation</Title>
  <Section position="8" start_page="1089" end_page="1089" type="concl">
    <SectionTitle>
8 Conclusion
</SectionTitle>
    <Paragraph position="0"> We have evaluated vm'ious statistical alignment models by conlparing the Viterbi alignment of the model with a human-made alignment. We have shown that by using inore sophisticated models the quality of the alignments improves significantly. Further improvements in producing better alignments are expected from using the HMM alignment model to bootstrap the fertility models, fronl making use of cognates, and from statistical alignment models that are based on word groups rather than single words.</Paragraph>
  </Section>
class="xml-element"></Paper>