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<Paper uid="C90-2044">
  <Title>Disambiguating Cue Phrases in Text and Speech</Title>
  <Section position="9" start_page="0" end_page="0" type="concl">
    <SectionTitle>
5 Discussion
</SectionTitle>
    <Paragraph position="0"> Our findings for the first stage of our single-speaker multi-cue phrase study support the intonational model of discourse/sentential characteristics of cue phrases which we proposed in \[8\]. Discourse uses of cue phrases fell into two groups: in one, the cue phrase was set apart as a separate intermediate phrase (possibly with other cue phrases); in the other, the cue phrase was first in its intermediate phrase (possibly preceded by other cue phrases) and either was deaccented or bore a L* pitch accent.</Paragraph>
    <Paragraph position="1"> Sentential uses were in general part of a larger intermediate phrase: if first in phrase, they bore a H* or complex pitch accent. The association between discourse/sentential models and discourse/sentential judgments is significant at the .0(/1 level. We also found that the tokens we found difficult to clas255 5 sify were those in which disambiguation relied solely upon pitch accent, rather than some combination of pitch accent and phrasing. Furthermore, we found that orthographic cues (from transcription) successfully disarnbiguate between discourse and sentential usage in 89.4% of cases in our pilot study. Part-of-speech was less successful in distinguishing discourse from sentential use, disambiguating only 75% of cases in the study.</Paragraph>
    <Paragraph position="2"> The disambiguating power of both our textual and our prosodic models has both theoretical and practical import. From a practical point of view, the construction of both text-based and prosodic models permit improvement in the generation of synthetic speech from unrestricted text \[9\]. With a prosodic model, we know how to convey discourse/sentential distinctions; with a text-based model, we know when to convey such distinctions. From a theoretical point of view, our findings demonstrate the feasibility of cue phrase disambiguation in both text and speech and provide a model for how that disambiguation might be done. Furthermore, these results strengthen the claim that the discourse structures crucial to computational models of interaction can indeed be identified.</Paragraph>
  </Section>
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