English

AMII: Adaptive Multimodal Inter-personal and Intra-personal Model for Adapted Behavior Synthesis

Human-Computer Interaction 2023-05-22 v1 Machine Learning Sound Audio and Speech Processing

Abstract

Socially Interactive Agents (SIAs) are physical or virtual embodied agents that display similar behavior as human multimodal behavior. Modeling SIAs' non-verbal behavior, such as speech and facial gestures, has always been a challenging task, given that a SIA can take the role of a speaker or a listener. A SIA must emit appropriate behavior adapted to its own speech, its previous behaviors (intra-personal), and the User's behaviors (inter-personal) for both roles. We propose AMII, a novel approach to synthesize adaptive facial gestures for SIAs while interacting with Users and acting interchangeably as a speaker or as a listener. AMII is characterized by modality memory encoding schema - where modality corresponds to either speech or facial gestures - and makes use of attention mechanisms to capture the intra-personal and inter-personal relationships. We validate our approach by conducting objective evaluations and comparing it with the state-of-the-art approaches.

Keywords

Cite

@article{arxiv.2305.11310,
  title  = {AMII: Adaptive Multimodal Inter-personal and Intra-personal Model for Adapted Behavior Synthesis},
  author = {Jieyeon Woo and Mireille Fares and Catherine Pelachaud and Catherine Achard},
  journal= {arXiv preprint arXiv:2305.11310},
  year   = {2023}
}

Comments

8 pages, 1 figure