Combining multiple knowledge sources for discourse segmentation

  • Authors:
  • Diane J. Litman;Rebecca J. Passonneau

  • Affiliations:
  • AT&T Bell Laboratories, Murray Hill, NJ;Bellcore, Morristown, NJ

  • Venue:
  • ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
  • Year:
  • 1995

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Abstract

We predict discourse segment boundaries from linguistic features of utterances, using a corpus of spoken narratives as data. We present two methods for developing segmentation algorithms from training data: hand tuning and machine learning. When multiple types of features are used, results approach human performance on an independent test set (both methods), and using cross-validation (machine learning).