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<Paper uid="W05-0813">
  <Title>Symmetric Probabilistic Alignment</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We recently decided to develop a new alignment algorithm for the purpose of improving our Example-Based Machine Translation (EBMT) system's performance, since subsentential alignment is critical in locating the correct translation for a matched fragment of the input. Unlike most algorithms in the literature, this</Paragraph>
    <Section position="1" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
new Symmetric Probabilistic Alignment
</SectionTitle>
      <Paragraph position="0"> (SPA) algorithm treats the source and target languages in a symmetric fashion.</Paragraph>
      <Paragraph position="1"> In this short paper, we outline our basic algorithm and some extensions for using context and positional information, and compare its alignment accuracy on the Romanian-English data for the shared task with IBM Model 4 and the reported results from the prior workshop.</Paragraph>
    </Section>
  </Section>
class="xml-element"></Paper>