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Paper Information

lrec2022-main-245

Annotating Interruption in Dyadic Human Interaction

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Title

Annotating Interruption in Dyadic Human Interaction

Abstract

Integrating the existing interruption and turn switch classification methods, we propose a new annotation schema to annotate different types of interruptions through timeliness, switch accomplishment and speech content level. The proposed method is able to distinguish smooth turn exchange, backchannel and interruption (including interruption types) and to annotate dyadic conversation. We annotated the French part of NoXi corpus with the proposed structure and use these annotations to study the probability distribution and duration of each turn switch type.


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