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<Paper uid="W04-2904">
  <Title>Scoring Algorithms for Wordspotting Systems</Title>
  <Section position="3" start_page="0" end_page="0" type="intro">
    <SectionTitle>
2 Assumptions
</SectionTitle>
    <Paragraph position="0"> In order to derive a scoring algorithm, a key assumption must be made by the wordspotting algorithm: each match must have a numeric score associated with it. In addition, there must be some theoretical basis for an additive decomposition of this score. This decomposition is given</Paragraph>
    <Paragraph position="2"> where R(q) is the score returned by query q, and R(q)l is the score associated with the lth phoneme in the query.</Paragraph>
    <Paragraph position="3"> With this assumption, we also assume that these components can be modeled with a Gaussian distribution with dependence on whether the match is truly a hit or a miss.</Paragraph>
    <Paragraph position="4"> The distributions are then given by</Paragraph>
    <Paragraph position="6"> where S(q)l is the lth phoneme in query q. In this model, the means, u are dependent on the phoneme, but the variance, s2, is not. Using the additive model, the raw scores are distributed by</Paragraph>
  </Section>
class="xml-element"></Paper>