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<Paper uid="P92-1008">
  <Title>INTEGRATING MULTIPLE KNOWLEDGE SOURCES FOR DETECTION AND CORRECTION OF REPAIRS IN HUMAN-COMPUTER DIALOG*</Title>
  <Section position="10" start_page="62" end_page="62" type="concl">
    <SectionTitle>
CONCLUSION
</SectionTitle>
    <Paragraph position="0"> In summary, disfluencies occur at high enough rates in human-computer dialog to merit consideration. In contrast to earlier approaches, we have made it our goal to detect and correct repairs automatically, without assuming an explicit edit signal. Without such an edit signal, however, repairs are easily confused both with false positives and with other repairs. Preliminary results show that pattern matching is effective at detecting repairs without excessive overgeneration. Our syntactic/semantic approaches are quite accurate at detecting repairs and correcting them. Acoustics is a third source of information that can be tapped to provide evidence about the existence of a repair.</Paragraph>
    <Paragraph position="1"> While none of these knowledge sources by itself is sufficient, we propose that by combining them, and possibly others, we can greatly enhance our ability to detect and correct repairs. As a next step, we intend to explore additional aspects of the syntax and semantics of repairs, analyze further acoustic patterns, and pursue the question of how best to integrate information from these multiple knowledge sources.</Paragraph>
  </Section>
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