Automatic detection of syllable boundaries combining the advantages of treebank and bracketed corpora training

  • Authors:
  • Karin Müller

  • Affiliations:
  • University of Stuttgart, Stuttgart, Germany

  • Venue:
  • ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
  • Year:
  • 2001

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Abstract

An approach to automatic detection of syllable boundaries is presented. We demonstrate the use of several manually constructed grammars trained with a novel algorithm combining the advantages of treebank and bracketed corpora training. We investigate the effect of the training corpus size on the performance of our system. The evaluation shows that a hand-written grammar performs better on finding syllable boundaries than does a treebank grammar.