<?xml version="1.0" standalone="yes"?>
<Paper uid="W03-1703">
  <Title>Utterance Segmentation Using Combined Approach Based on Bi-directional N-gram and Maximum Entropy</Title>
  <Section position="6" start_page="21" end_page="21" type="concl">
    <SectionTitle>
5 Conclusion
</SectionTitle>
    <Paragraph position="0"> This paper proposes a reverse N-gram algorithm, a bi-directional N-gram algorithm and a Maximum-entropy-weighted Bi-directional N-gram algorithm for utterance segmentation. The experimental results for both Chinese and English utterance segmentation show that MEBN significantly outperforms the usual N-gram algorithm. This is because MEBN takes into account both the left and right contexts of candidate sites: it integrates the left-to-right N-gram algorithm and the right-to-left N-gram algorithm with appropriate weights, using clues on the sites' lexical context, as modeled by maximum entropy.</Paragraph>
  </Section>
class="xml-element"></Paper>