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<Paper uid="P97-1034">
  <Title>Tracking Initiative in Collaborative Dialogue Interactions</Title>
  <Section position="7" start_page="268" end_page="268" type="concl">
    <SectionTitle>
5 Conclusions
</SectionTitle>
    <Paragraph position="0"> This paper discussed a model for tracking initiative between participants in mixed-initiative dialogue interactions. We showed that distinguishing between task and dialogue initiatives allows us to model phenomena in collaborative dialogues that existing systems are unable to explain. We presented eight types of cues that affect initiative shifts in dialogues, and showed how our model 1degIn the maptask domain, the task initiative remains with one agent, the instruction giver, throughout the dialogue.</Paragraph>
    <Paragraph position="1"> predicts initiative shifts based on the current initiative holders and and the effects that observed cues have on changing them. Our experiments show that by utilizing the constant-increment-with-counter adjustment method in determining the basic probability assignments for each cue, the system can correctly predict the task and dialogue initiative holders 99.1% and 87.8% of the time, respectively, in the TRAINS91 corpus, compared to 96.8% and 74.9% without the use of cues. The differences between these results are shown to be statistically significant using Cochran's Q test. In addition, we demonstrated the generality of our model by applying it to dialogues in different application environments. The results indicate that although the basic probability assignments may be sensitive to application environments, the use of cues in the prediction process significantly improves the system' s performance.</Paragraph>
  </Section>
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