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<Paper uid="C94-2198">
  <Title>WORD CLASS DISCOVERY FOR POSTPROCESSING CHINESE HANDWRITING RECOGNITION</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
WORD CLASS DISCOVERY FOR POSTPROCESSING
CHINESE HANDWRITING RECOGNITION
Chao-Huang Chang
</SectionTitle>
    <Paragraph position="0"> E000/CCI~, Building 11, Industrial Technology Research Institute Chutung, Hsinchu 31015, TAIWAN, R.O.C.</Paragraph>
    <Paragraph position="1"> Summary This article presents a novel Chinese class n-gram model for contextual postprocessing of haudwriting recognition results. The word classes in the model are automatically discovered by a corpus-based simulated anuealing procedure. Three other language models, least-word, word-frequency, and the powerflfl inter-word character bigram model, have been constructed for comparison. Extensive experiments on large text corpora show that the discovered class bigram model outperforms the other three competing models.</Paragraph>
  </Section>
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