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<Paper uid="P97-1047">
  <Title>Decoding Algorithm in Statistical Machine Translation</Title>
  <Section position="8" start_page="371" end_page="371" type="concl">
    <SectionTitle>
6 Conclusions
</SectionTitle>
    <Paragraph position="0"> We have reported a stack decoding algorithm for the IBM statistical translation model 2 and a simplified model. Because the simplified model has fewer uarameters and does not have to posit hypotheses with the same prefixes but different length, it out-performed the IBM model 2 with regard to both accuracy and efficiency, especially in our application that lacks a massive amount of training data. In most cases, the erroneous outputs from the decoder have a higher score than the human made translations. Therefore it is less likely that the decoder is a major contributor of translation errors.</Paragraph>
  </Section>
class="xml-element"></Paper>