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<Paper uid="W02-1405">
  <Title>Improving a general-purpose Statistical Translation Engine by Terminological lexicons</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> The past decade has witnessed exciting work in the fleld of Statistical Machine Translation (SMT). However, accurate evaluation of its potential in real-life contexts is still a questionable issue.</Paragraph>
    <Paragraph position="1"> In this study, we investigate the behavior of an SMT engine faced with a corpus far difierent from the one it has been trained on. We show that terminological databases are obvious resources that should be used to boost the performance of a statistical engine. We propose and evaluate a way of integrating terminology into a SMT engine which yields a signiflcant reduction in word error rate.</Paragraph>
  </Section>
class="xml-element"></Paper>