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<Paper uid="W06-3117">
  <Title>Stochastic Inversion Transduction Grammars for Obtaining Word Phrases for Phrase-based Statistical Machine Translation</Title>
  <Section position="6" start_page="132" end_page="132" type="concl">
    <SectionTitle>
5 Conclusions
</SectionTitle>
    <Paragraph position="0"> In this work, we have explored the problem of obtaining word phrases for phrase-based machine translation systems from SITGs. We have described how the parsing algorithms for this formalism can be modified in order to take into account a bracketed corpus. If bracketed corpora are used the time complexity can decrease notably and large tasks can be considered. Experiments were reported for the Europarl corpus, and the results obtained were competitive. null For future work, we propose to work along different lines: first, to incorporate new linguistic information in both the parsing algorithm and in the aligned corpus; second, to obtain better SITGs from aligned bilingual corpora; an third, to improve the SITG by estimating the syntactic rules. We also intend to address other machine translation tasks.</Paragraph>
  </Section>
class="xml-element"></Paper>