<?xml version="1.0" standalone="yes"?>
<Paper uid="H94-1086">
  <Title>On-Line Cursive Handwriting Recognition Using Hidden Markov Models and Statistical Grammars</Title>
  <Section position="7" start_page="434" end_page="434" type="concl">
    <SectionTitle>
6. CONCLUSION
</SectionTitle>
    <Paragraph position="0"> We have shown that a HMM based speech recognition system can perform well on on-line cursive handwriting tasks without needing segmentation of training or test data. On a 25,595 word, 86 symbol, writer dependent task over six writers, an average of 4.1 % word error rate and an average of 1.4% character error rate was achieved. With some simple tuning, significant reduction in these error rates is expected. These findings suggest that HMM-based methods combined with statistical grammars will prove to be a very powerful tool in handwriting recognition.</Paragraph>
  </Section>
class="xml-element"></Paper>