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<Paper uid="W97-0606">
  <Title>Clarification Dialogues as Measure to Increase Robustness in a Spoken Dialogue System</Title>
  <Section position="5" start_page="35" end_page="35" type="relat">
    <SectionTitle>
4 Related Work
</SectionTitle>
    <Paragraph position="0"> Various approaches have been proposed to cope with problems of unexpected, wrong or missing input: (Allen et al., 1996) decided to choose the most specific possible option when the system is confronted with ambiguities. To handle this problem the TRAINS system tries to recognize and exploit corrections included in follow-up dialogue actions. (Qu et al., 1997) describe a method to minimize cumulative error in the ENTHUSIAST system. To this end dialogue context, statistical information, and grammar information are taken into account to process and predict dialogue states, where non-contextual information is preferred over contextual information when processing conflicts occur.</Paragraph>
    <Paragraph position="1"> While clarification dialogues are common in human-machine dialogues (see e.g. (Eckert and Mc-Glashan, 1993)), they are a rather recent development in systems that support computer-mediated interactions. To our knowledge the VERBMOBIL prototype is the first system that uses repair methods, defaults and clarification dialogues to recover from problematic system states.</Paragraph>
  </Section>
class="xml-element"></Paper>