Annotating Interruption in Dyadic Human Interaction

Liu Yang (1) , Catherine Achard (1) , Catherine Pelachaud (1)

1 ISIR - Institut des Systèmes Intelligents et de Robotique

Integrating the existing interruption and turn switch classification methods, we propose a new annotation schema to annotate different types of interruptions through timeliness, accomplishment and speech content level. 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.

Keywords: Interruption Annotation; Turn-taking; Dyadic Conversation

Domains: Computer Science [cs]; Human-Computer Interaction [cs.HC]

Liu Yang, Catherine Achard, Catherine Pelachaud. Annotating Interruption in Dyadic Human Interaction. Thirteenth Language Resources and Evaluation Conference, LREC, 2022, Marseille, France. ⟨hal-03855440⟩