Analysis and classification of cooperative and competitive dialogs

Uwe D. Reichel, Nina Pörner, Dianne Nowack, Jennifer Cole

Research output: Contribution to journalConference article

Abstract

Cooperative and competitive game dialogs are comparatively examined with respect to temporal, basic text-based, and dialog act characteristics. The condition-specific speaker strategies are amongst others well reflected in distinct dialog act probability distributions, which are discussed in the context of the Gricean Cooperative Principle and of Relevance Theory. Based on the extracted features, we trained Bayes classifiers and support vector machines to predict the dialog condition, that yielded accuracies from 90 to 100%. Taken together the simplicity of the condition classification task and its probabilistic expressiveness for dialog acts suggests a two-stage classification of condition and dialog acts.

Original languageEnglish (US)
Pages (from-to)3056-3060
Number of pages5
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Volume2015-January
StatePublished - Jan 1 2015
Event16th Annual Conference of the International Speech Communication Association, INTERSPEECH 2015 - Dresden, Germany
Duration: Sep 6 2015Sep 10 2015

Keywords

  • Cooperative principle
  • Dialog acts
  • Gricean maxims
  • Machine learning

ASJC Scopus subject areas

  • Language and Linguistics
  • Human-Computer Interaction
  • Signal Processing
  • Software
  • Modeling and Simulation

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