Tears and fears: modeling emotions and emotional behaviors in synthetic agents
Proceedings of the fifth international conference on Autonomous agents
BEAT: the Behavior Expression Animation Toolkit
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Influences and Embodied Conversational Agents
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Multimodal expressive embodied conversational agents
Proceedings of the 13th annual ACM international conference on Multimedia
Personality and Emotion-Based High-Level Control of Affective Story Characters
IEEE Transactions on Visualization and Computer Graphics
Automated generation of non-verbal behavior for virtual embodied characters
Proceedings of the 9th international conference on Multimodal interfaces
SmartBody: behavior realization for embodied conversational agents
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Towards a common framework for multimodal generation: the behavior markup language
IVA'06 Proceedings of the 6th international conference on Intelligent Virtual Agents
Agent communication for believable human-like interactions between virtual characters
CAVE'12 Proceedings of the First international conference on Cognitive Agents for Virtual Environments
| Hi-index | 0.00 |
Communication, along with other factors, varies with gender. Significant work as been done around embodied conversational agents (ECAs) verbal and non-verbal behaviour but gender issue has often been ignored. Yet, together with personality, culture and other factors, gender is a feature that impacts the perception and thus the believability of the characters. The main goal of this work is to understand how gender can be provided to ECAs, and provide a very simple model that allows for existing tools to overcome such limitation. The proposed system was developed around SAIBA Framework using SmartBody as the behavior realizer and tries to address this problem by adding a set of involuntary gender specific movements to the agents behaviour in an automatic manner. This is achieved by revising and complementing the work done by the existing non-verbal behaviour generators. Focusing mainly on nonverbal behaviour, our agents with gender were tested to see if users were able to perceive the gender bias of the behaviours being performed. Results have shown that gender is correctly perceived, and also has effects when paired with an accurate gender appearance.