The Importance of Multimodal Emotion Conditioning and Affect Consistency for Embodied Conversational Agents
Che-Jui Chang, Samuel S. Sohn, Sen Zhang, Rajath Jayashankar, Muhammad, Usman, Mubbasir Kapadia

TL;DR
This paper introduces ACTOR, a framework for generating multimodal behaviors in embodied conversational agents that are affectively consistent, significantly improving the perception of emotions and expressiveness in human-agent interactions.
Contribution
The paper presents a novel affect-consistent multimodal behavior generation framework, addressing the challenge of producing expressive, emotionally coherent responses in embodied agents.
Findings
Affect-consistent behaviors are perceived as more expressive.
Inconsistent affects reduce perception of driving emotions.
Affect consistency enhances overall emotional perception in agents.
Abstract
Previous studies regarding the perception of emotions for embodied virtual agents have shown the effectiveness of using virtual characters in conveying emotions through interactions with humans. However, creating an autonomous embodied conversational agent with expressive behaviors presents two major challenges. The first challenge is the difficulty of synthesizing the conversational behaviors for each modality that are as expressive as real human behaviors. The second challenge is that the affects are modeled independently, which makes it difficult to generate multimodal responses with consistent emotions across all modalities. In this work, we propose a conceptual framework, ACTOR (Affect-Consistent mulTimodal behaviOR generation), that aims to increase the perception of affects by generating multimodal behaviors conditioned on a consistent driving affect. We have conducted a user…
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