Towards a Conversation-Analytic Taxonomy of Speech Overlap

Abstract

We present a taxonomy for classifying speech overlap in natural language dialogue. The scheme classifies overlap on the basis of several features, including onset point, local dialogue history, and management behavior. We describe the various dimensions of this scheme and show how it was applied to a corpus of remote, collaborative dialogue. Moving forward, this will serve as the basis for a computational model of speech overlap, and for use in artificial agents that interact with humans in social settings.

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