An Expressive Virtual Audience with Flexible Behavioral Styles

作者：Kang Ni^*; Brinkman Willem Paul; van Riemsdijk M Birna; Neerincx Mark A

来源：IEEE Transactions on Affective Computing, 2013, 4(4): 326-340.

DOI：10.1109/TAFFC.2013.2297104

• Expressive listening behavior
• parameterized audience model
• public speaking
• virtual agents

Currently, expressive virtual humans are used in psychological research, training, and psychotherapy. However, the behavior of these virtual humans is usually scripted and therefore cannot be modified freely at runtime. To address this, we created a virtual audience with parameterized behavioral styles. This paper presents a parameterized audience model based on probabilistic models abstracted from the observation of real human audiences dn (n = 16) The audience%26apos;s behavioral style is controlled by model parameters that define virtual humans%26apos; moods, attitudes, and personalities. Employing these parameters as predictors, the audience model significantly predicts audience behavior. To investigate if people can recognize the designed behavioral styles generated by this model, 12 audience styles were evaluated by two groups of participants. One group dn (n = 22) was asked to describe the virtual audience freely, and the other group dn (n = 22) was asked to rate the audiences on eight dimensions. The results indicated that people could recognize different audience attitudes and even perceive the different degrees of certain audience attitudes. In conclusion, the audience model can generate expressive behavior to show different attitudes by modulating model parameters.

• 出版日期2013-12