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<Paper uid="H91-1020">
  <Title>STOCHASTIC REPRESENTATION OF CONCEPTUAL STRUCTURE IN THE ATIS TASK</Title>
  <Section position="7" start_page="123" end_page="123" type="concl">
    <SectionTitle>
CONCLUSIONS
</SectionTitle>
    <Paragraph position="0"> We proposed a very simple semantic grammar for the ATIS task. The grammar was designed to be rich enough to handle most queries, but limited in certain ways so as to facilitate parsing by very simple and well-understood HMM methods. The advantages of this approach are its straightforward integration with an HMM based speech recognizer, and its capability of learning from examples. Even with an extremely small training set, the system was able to assign the correct analysis to more than 80% of the class A sentences in both the JUN-90 and FEB-91 test sets.</Paragraph>
    <Paragraph position="1"> The authors gratefully acknowledge the helpful advice and consultation of Ken Church, Alexandra Gertner, A1 Gorin, Fernando Pereira, and Evelyne Tzoukerman.</Paragraph>
  </Section>
class="xml-element"></Paper>