1 research outputs found
Using Virtual Humans to Understand Real Ones
Human interactions are characterized by explicit as well as implicit channels
of communication. While the explicit channel transmits overt messages, the
implicit ones transmit hidden messages about the communicator (e.g., his/her
intentions and attitudes). There is a growing consensus that providing a
computer with the ability to manipulate implicit affective cues should allow
for a more meaningful and natural way of studying particular non-verbal signals
of human-human communications by human-computer interactions. In this pilot
study, we created a non-dynamic human-computer interaction while manipulating
three specific non-verbal channels of communication: gaze pattern, facial
expression, and gesture. Participants rated the virtual agent on affective
dimensional scales (pleasure, arousal, and dominance) while their physiological
signal (electrodermal activity, EDA) was captured during the interaction.
Assessment of the behavioral data revealed a significant and complex three-way
interaction between gaze, gesture, and facial configuration on the dimension of
pleasure, as well as a main effect of gesture on the dimension of dominance.
These results suggest a complex relationship between different non-verbal cues
and the social context in which they are interpreted. Qualifying considerations
as well as possible next steps are further discussed in light of these
exploratory findings