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<Paper uid="W98-1122">
  <Title>Automatic Acquisition of Phrase Grammars for Stochastic Language Modeling</Title>
  <Section position="8" start_page="195" end_page="195" type="concl">
    <SectionTitle>
6 Conclusions
</SectionTitle>
    <Paragraph position="0"> In this paper, we have presented a novel approach to automatically combine the acquisition of grammar fragments for language modeling. The phrase grammar learning is decomposed into two sub-problems, namely the phrase acquisition and feature selection.</Paragraph>
    <Paragraph position="1"> The phrase acquisition is based on entropy minimization and the feature selection is driven by the entropy reduction principle. This integration results in the learning of stochastic phrase-grammar fragments, which are then context dependent trained on the corpus at hand. We also demonstrated that a phrase-grammar based language model significantly outperformed a phrase-based language model in an end-to-end evaluation of a spoken language application. null</Paragraph>
  </Section>
class="xml-element"></Paper>