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<Paper uid="W97-0402">
  <Title>A Dialogue Analysis Model with Statistical Speech Act Processing for Dialogue Machine Translation*</Title>
  <Section position="8" start_page="14" end_page="14" type="concl">
    <SectionTitle>
6 Conclusions
</SectionTitle>
    <Paragraph position="0"> In this paper, we described an efficient dialogue analysis model with statistical speech act processing. We proposed a statistical method to decide a speech act of a sentence and to maintain a discourse structure. This model uses the surface syntactic patterns of the sentence and N-gram of speech acts of the sentences which are discourse structurally recent to tile sentence. Our experimental results with trigram showed that the proposed model achieved 78.59 % accuracy for the top candidate and 99.06 % for the top four candidates although the size of the training corpus is relatively small. This model is weaker than the dialogue analysis model which uses many difference source of knowledge. However, it is more efficient and robust, and easy to be scaled up. We believe that this kind of statistical approach can be integrated with other approaches for an efficient and robust analysis of dialogues.</Paragraph>
  </Section>
class="xml-element"></Paper>