Chen Wang

Address

Computer Vision and Multimedia Laboratory

Computer Science Department

University of Geneva

7 route de Drize, Battelle, Building A

CH-1227 Carouge

Office: #227, 1st Floor Battelle A

E-mail: Chen.Wang@unige.ch 

Tel: 0223790176

Function

PhD student and research assistant

Teaching

Interaction multimodale et affective

Imagerie numerique

System Informatique

Research

Research projects

Seconds that matter: Managing First Impressions for a more Engaging Virtual Agent

In any encounter the first moments are critical and the impressions that we form of others matter. These impressions tend to last and affect the interaction experience. The goal of this project is to build an anthropomorphic virtual character (ECA - Embodied Conversational Agent) able to make the best possible first impression on a user, thus effectively engaging him or her in an interaction. This goal will be realized by building an affective loop which ties the behavior of the ECA to the actual emotional reactions of the user facing it in real-time. This will give rise to an ECA capable of managing their first impressions on users. We focus on the identification and modeling of the nonverbal behavior, towards exhibiting, managing and maintaining impressions of two important socio-cognitive dimensions in the first minutes of interaction with a user. These dimensions are warmth (i.e. being friendly, agreeable, engaging and approachable) and competence (i.e. appear skilled, knowledgeable on a given topic). The IMPRESSIONS project has humanistic and computational components. The analysis and modeling of nonverbal communicative behavior is drawn from existing literature in sociology and psychology, as well as from new data gathered from controlled user studies. The computational component implements those models in a virtual agent, resulting in believable and effective social behaviors. Furthermore, user’s behaviors and physiological signals will help the agent managing the desired impressions. The analysis of multimodal signals is valuable to assess the user’s affective states, to determine the quality of the interaction, and, ultimately, for assessing the impressions that the user has formed of the agent. Results undergo a thorough user evaluation.

Publications

 

Conference Presentations

  • Wang, C., Lopes,P., Pun, T., & Chanel, G. (2019). Multimodal Analysis of Impressions for a More Engaging Virtual Agent, ISRE 2019.

Posters

  • Wang, C., Pun, T., & Chanel, G. (2019). Impression Detection From Face and Eye Gaze, Swiss Winter School on Deep Learning 2019.
  • Wang, C., Pun, T., & Chanel, G. (2019). Impression Detection From Face and Eye Gaze, Swiss Center for Affective Science Annual Research Forum 2019
  • Wang, C., Pun, T., & Chanel, G. (2018). A Multimodal Database for Impression Detection and Prediction, Swiss Center for Affective Science Annual Research Forum 2018