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Multimodal Analysis of Interruptions

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Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Anthropometry, Human Behavior, and Communication (HCII 2022)

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Abstract

During an interaction, interactants exchange speaking turns. Exchanges can be done smoothly or through interruptions. Listeners can display backchannels, send signals to grab the speaking turn, wait for the speaker to yield the turn, or even interrupt and grab the speaking turn. Interruptions are very frequent in natural interactions. To create believable and engaging interaction between human interactants and embodied conversational agent ECA, it is important to endow virtual agent with the capability to manage interruptions, that is to have the ability to interrupt, but also to react to an interruption. As a first step, we focus on the later one where the agent is able to perceive and interpret the user’s multimodal behaviors as either an attempt or not to take the turn. To this aim, we annotate, analyse and characterize interruptions in human-human conversations. In this paper, we describe our annotation schema that embeds different types of interruptions. We then provide an analysis of multimodal features, focusing of prosodic features (F0 and loudness) and body (head and hand) activity, to characterize interruptions.

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Acknowledgements

This work was performed as part of ANR-JST-CREST TAPAS and ANR-JST-DFG PANORAMA project.

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Authors and Affiliations

  1. Institut des Systèmes Intelligents et de Robotique (CNRS-ISIR), Sorbonne University, 75005, Paris, France

    Liu Yang, Catherine Achard & Catherine Pelachaud

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  1. Liu Yang
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  2. Catherine Achard
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Correspondence to Liu Yang .

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  1. School of Industrial Engineering, Purdue University, West Lafayette, IN, USA

    Vincent G. Duffy

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Yang, L., Achard, C., Pelachaud, C. (2022). Multimodal Analysis of Interruptions. In: Duffy, V.G. (eds) Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Anthropometry, Human Behavior, and Communication. HCII 2022. Lecture Notes in Computer Science, vol 13319. Springer, Cham. https://doi.org/10.1007/978-3-031-05890-5_24

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  • DOI: https://doi.org/10.1007/978-3-031-05890-5_24

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