Visible to the public Sequence-based Multimodal Behavior Modeling for Social Agents

TitleSequence-based Multimodal Behavior Modeling for Social Agents
Publication TypeConference Paper
Year of Publication2016
AuthorsDermouche, Soumia, Pelachaud, Catherine
Conference NameProceedings of the 18th ACM International Conference on Multimodal Interaction
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-4556-9
Keywordshuman factors, interpersonal attitudes, non-verbal behavior, pubcrawl, Scalability, Social Agents, Temporal Sequence Mining, virtual agent
Abstract

The goal of this work is to model a virtual character able to converse with different interpersonal attitudes. To build our model, we rely on the analysis of multimodal corpora of non-verbal behaviors. The interpretation of these behaviors depends on how they are sequenced (order) and distributed over time. To encompass the dynamics of non-verbal signals across both modalities and time, we make use of temporal sequence mining. Specifically, we propose a new algorithm for temporal sequence extraction. We apply our algorithm to extract temporal patterns of non-verbal behaviors expressing interpersonal attitudes from a corpus of job interviews. We demonstrate the efficiency of our algorithm in terms of significant accuracy improvement over the state-of-the-art algorithms.

URLhttp://doi.acm.org/10.1145/2993148.2993180
DOI10.1145/2993148.2993180
Citation Keydermouche_sequence-based_2016