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<Paper uid="W98-0905">
  <Title>Front Back Consistency Overgeneration</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> This paper describes a formal approach and a practical learning method for automatically acquiring phonotactic constraints encoded as finite automata. It is proposed that the use of different classes of syllables with class-specific intra-syl\]abic phonotactics results in a more accurate hypothesis of a language's phonological grammar than the single syllable class traditionally used. Intra-syllabic constraints are encoded as acyclic finite automata with input alphabets of phonemic symbols. These automata in turn form the transitions in cyclic finite automata that encode the inter-syllabic constraints of word-level phonology. A genetic algorithm is used to automatically construct finite automata from training sets of symbol strings.</Paragraph>
    <Paragraph position="1"> Results are reported for a set of German syllables and a set of Russian bisyllabic feminine nouns.</Paragraph>
  </Section>
class="xml-element"></Paper>