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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="4" start_page="0" end_page="10" type="intro">
    <SectionTitle>
2 Motivation
</SectionTitle>
    <Paragraph position="0"> Translation of dialogues often requires the analysis of contexts. That is, a surface utterance may be translated differently depending on context. In this  section, we present some motivational examples. The word 'yey q in Korean has a number of English expression such as 'yes', 'no', 'O.K:', 'Hello', 'thanks', and so on (Jae-woong Choe 1996). When the speech act of the utterance 'yey' is response, it must be translated as 'yes' or 'no'. On the other hand, when the speech act of the utterance is accept, it must be translated as 'O.K.'. It is even used as greeting or opening in Korean. In this case, 'Hello' is an appropriate expression in English.</Paragraph>
    <Paragraph position="1"> The verb 'kulehsupnita' in Korean, also, may be translated differently depending on context.</Paragraph>
    <Paragraph position="2"> Kulehsupnila is used to accept the previous utterance in Korean. In this case, it must be translated differently depending on context. The following dialogue examples show such cases.</Paragraph>
    <Paragraph position="3">  To differentiate such cases, a translation system must analyze the context of a dialogue. Since a dialogue has a hierarchical structure than a linear structure, the discourse structure of a dialogue must be analyzed to reflect the context in translation. There are the previous plan-based approaches for analyzing context in dialogues. Since it is very difficult to have a complete knowledge, it is not easy to find a correct analysis using such knowledge bases. In this paper, we propose a statistical dialogue analysis model based on speech acts for dialogue machine translation. Such 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 minimal approach is more appropriate for a translation system.</Paragraph>
  </Section>
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