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<?xml version="1.0" standalone="yes"?>
<Paper uid="H94-1014">
  <Title>Language Modeling with Sentence-Level Mixtures</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
ABSTRACT
</SectionTitle>
    <Paragraph position="0"> This paperintroduces a simple mixtare language model that attempts to capture long distance conslraints in a sentence or paragraph. The model is an m-component mixture of Irigram models. The models were constructed using a 5K vocabulary and trained using a 76 million word Wail Street Journal text corpus. Using the BU recognition system, experiments show a 7% improvement in recognition accuracy with the mixture trigram models as compared to using a Irigram model.</Paragraph>
  </Section>
class="xml-element"></Paper>
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