Latent semantic analysis for dialogue act classification

  • Authors:
  • Riccardo Serafin;Barbara Di Eugenio;Michael Glass

  • Affiliations:
  • University of Illinois, Chicago, IL;University of Illinois, Chicago, IL;Valparaiso University, Valparaiso, IN

  • Venue:
  • NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
  • Year:
  • 2003

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Abstract

This paper presents our experiments in applying Latent Semantic Analysis (LSA) to dialogue act classification. We employ both LSA proper and LSA augmented in two ways. We report results on DIAG, our own corpus of tutoring dialogues, and on the CallHome Spanish corpus. Our work has the theoretical goal of assessing whether LSA, an approach based only on raw text, can be improved by using additional features of the text.