Sequence-based Multimodal Behavior Modeling for Social Agents
Title | Sequence-based Multimodal Behavior Modeling for Social Agents |
Publication Type | Conference Paper |
Year of Publication | 2016 |
Authors | Dermouche, Soumia, Pelachaud, Catherine |
Conference Name | Proceedings of the 18th ACM International Conference on Multimodal Interaction |
Publisher | ACM |
Conference Location | New York, NY, USA |
ISBN Number | 978-1-4503-4556-9 |
Keywords | human 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. |
URL | http://doi.acm.org/10.1145/2993148.2993180 |
DOI | 10.1145/2993148.2993180 |
Citation Key | dermouche_sequence-based_2016 |