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<Paper uid="H01-1029">
  <Title>Fine-Grained Hidden Markov Modeling for Broadcast- News Story Segmentation</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
ABSTRACT
</SectionTitle>
    <Paragraph position="0"> We present the design and development of a Hidden Markov Model for the division of news broadcasts into story segments.</Paragraph>
    <Paragraph position="1"> Model topology, and the textual features used, are discussed, together with the non-parametric estimation techniques that were employed for obtaining estimates for both transition and observation probabilities. Visualization methods developed for the analysis of system performance are also presented.</Paragraph>
  </Section>
class="xml-element"></Paper>