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<Paper uid="H94-1074">
  <Title>Speech-Based Retrieval Using Semantic Co-Occurrence Filtering</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
ABSTRACT
</SectionTitle>
    <Paragraph position="0"> In this paper we demonstrate that speech recognition can be effectively applied to information retrieval (IR) applications.</Paragraph>
    <Paragraph position="1"> Our system exploits the fact that the intended words of a spoken query tend to co-occur in text documents in close proximity whereas word combinations that are the result of recognition errors are usually not semantically correlated and thus do not appear together. Termed &amp;quot;Semantic Co-occurrence Filtering&amp;quot; this enables the system to simultaneously disambiguate word hypotheses and find relevant text for retrieval.</Paragraph>
    <Paragraph position="2"> The system is built by integrating standard IR and speech recognition techniques. An evaluation of the system is preseated and we discuss several refinements to the functionality.</Paragraph>
  </Section>
class="xml-element"></Paper>