Combining multiple knowledge sources for discourse segmentation

Diane J. Litman, Rebecca J. Passonneau

Research output: Contribution to journalConference articlepeer-review

64 Scopus citations

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).

Original languageEnglish (US)
Pages (from-to)108-115
Number of pages8
JournalProceedings of the Annual Meeting of the Association for Computational Linguistics
Volume1995-June
StatePublished - 1995
Event33rd Annual Meeting of the Association for Computational Linguistics, ACL 1995 - Cambridge, United States
Duration: Jun 26 1995Jun 30 1995

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Linguistics and Language
  • Language and Linguistics

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