<?xml version="1.0" standalone="yes"?>
<Paper uid="C92-2080">
  <Title>TRANSLATION AMBIGUITY RESOLUTION BASED ON TEXT CORPORA OF SOURCE AND TARGET LANGUAGES</Title>
  <Section position="7" start_page="0" end_page="0" type="concl">
    <SectionTitle>
5 Conclusion
</SectionTitle>
    <Paragraph position="0"> We lu'oposed a new method DMAX Criteria (Double Maximize Criteria based on Dual Corpora) in this paper. It can select a suitable equivalent translation or meaning using the statistical data extracted from both source and target language corpora even when linguistic restrictions described in the dictionary or grammar cannot. The depen dency relation in the source language is reflected in the translated text through bilingual dictionary.</Paragraph>
    <Paragraph position="1"> Moreover, the nmthod has the following features:  1. It utilizes linguistic statistics as context infer motion in addition to logical restrictions effective for ambiguity resolution.</Paragraph>
    <Paragraph position="2"> 2. The source of the linguistic statistics is the dual corpora of source and target languages, not the bilingual corpora (the target language text doesn't have to be the translation of the source language text).</Paragraph>
    <Paragraph position="3"> 3. The linguistic statistics can be coml)uted sendautomatically in advance.</Paragraph>
    <Paragraph position="4"> 4. Tim linguistic statistics on the pairs of mean- null ing expressions are computed from the linguistic statistics in source and target language texts with the interlingua-based bilingmd dictlonary to resolve ambiguity in meaning inter-. pretation.</Paragraph>
    <Paragraph position="5"> Based on this method, we have carried out an experinmnt on a limited-scale translation system, attd confirmed eti~ctiveness of the method. We are preparing further experiments on a large-scMe dual corpora with PIVOT interlingua dictionary. Their result will he reported on another paper.</Paragraph>
  </Section>
class="xml-element"></Paper>