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<Paper uid="N04-4021">
  <Title>Feature-based Pronunciation Modeling for Speech Recognition</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We present an approach to pronunciation modeling in which the evolution of multiple linguistic feature streams is explicitly represented.</Paragraph>
    <Paragraph position="1"> This differs from phone-based models in that pronunciation variation is viewed as the result of feature asynchrony and changes in feature values, rather than phone substitutions, insertions, and deletions. We have implemented a flexible feature-based pronunciation model using dynamic Bayesian networks. In this paper, we describe our approach and report on a pilot experiment using phonetic transcriptions of utterances from the Switchboard corpus. The experimental results, as well as the model's qualitative behavior, suggest that this is a promising way of accounting for the types of pronunciation variation often seen in spontaneous speech.</Paragraph>
  </Section>
class="xml-element"></Paper>