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<Paper uid="P06-1025">
  <Title>Dependencies between Student State and Speech Recognition Problems in Spoken Tutoring Dialogues</Title>
  <Section position="12" start_page="198" end_page="199" type="concl">
    <SectionTitle>
7 Conclusions
</SectionTitle>
    <Paragraph position="0"> In this paper we analyze the interactions between SRP and three higher level dialogue factors that define our notion of student state: frustration/anger/hyperarticulation, certainty and correctness. Our analysis produces several interesting insights and strategies which confirm the  utility of the proposed approach. We show that user emotions interact with SRP and that the emotion annotation level affects the interactions we observe from the data, with finer-level emotions yielding more interactions and insights. We also find that tutoring, as a new domain for speech applications, brings forward new important factors for spoken dialogue design: certainty and correctness. Both factors interact with SRP and these interactions highlight an interesting design practice in the spoken tutoring applications: the tradeoff between the pedagogical value of asking difficult questions and the system's ability to recognize the student answer (at least in our system). The particularities of the tutoring domain also suggest favoring misrecognitions over rejections to reduce the negative impact of asking to repeat after rejections.</Paragraph>
    <Paragraph position="1"> In our future work, we plan to move to the third step of our approach: testing the strategies suggested by our results. For example, we will implement a new version of ITSPOKE that never rejects the student turn. Next, the current version and the new version will be compared with respect to users' emotional response. Similarly, to test the tradeoff hypothesis, we will implement a version of ITSPOKE that asks difficult questions first and then falls back to simpler questions. A comparison of the two versions in terms of the number of SRP can be used for validation.</Paragraph>
    <Paragraph position="2"> While our results might be dependent on the tutoring system used in this experiment, we believe that our findings can be of interest to practitioners building similar voice-based applications. Moreover, our approach can be applied easily to studying other systems.</Paragraph>
  </Section>
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