An expressive virtual audience with flexible behavioral styles

An expressive virtual audience with flexible behavioral styles

Kang, N.
Brinkman, W.P.
van Riemsdijk, M.B.
Neerincx, M.A.

2013

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 (n = 16). The audience's behavioral style is controlled by model parameters that define virtual humans' 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 (n = 22) was asked to describe the virtual audience freely, and the other group (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. © 2010-2012 IEEE.

Human
PCS - Perceptual and Cognitive Systems
BSS - Behavioural and Societal Sciences
Virtual environments and Gaming
Information Society
Expressive listening behavior
Parameterized audience model
Public speaking
Virtual agents

http://resolver.tudelft.nl/uuid:bf790abe-acd6-48fc-8d8b-ee214196f287

https://doi.org/10.1109/taffc.2013.2297104

493091

Institute of Electrical and Electronics Engineers Inc.

1949-3045

IEEE Transactions on Affective Computing, 4 (4), 326-340

6714373

article