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<Paper uid="W97-1014">
  <Title>Word Triggers and the EM Algorithm</Title>
  <Section position="7" start_page="0" end_page="0" type="concl">
    <SectionTitle>
5 Conclusions
</SectionTitle>
    <Paragraph position="0"> We have presented a model and an algorithm for training a multi-word trigger model along with some experimental evaluations. The results can be summerized as follows: (r) The trigger parameters for all word triggers are jointly trained using the EM algorithm. This leads to a systematic (although small) improvement over the condition that each trigger parameter is trained separately.</Paragraph>
    <Paragraph position="1"> * The word-trigger model is used in combination with a full language model (m-gram/cache) .</Paragraph>
    <Paragraph position="2"> Thus the perplexity is reduced from 138.9 to 127.2 for the 5-million training corpus and from 92.2 to 87.4 for the 39-million corpus.</Paragraph>
  </Section>
class="xml-element"></Paper>