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<Paper uid="P06-2065">
  <Title>Unsupervised Analysis for Decipherment Problems</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We study a number of natural language decipherment problems using unsupervised learning. These include letter substitution ciphers, character code conversion, phonetic decipherment, and word-based ciphers with relevance to machine translation. Straightforward unsupervised learning techniques most often fail on the rst try, so we describe techniques for understanding errors and signi cantly increasing performance.</Paragraph>
  </Section>
class="xml-element"></Paper>