Analysis and classification of cooperative and competitive dialogs

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.

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