University of Michigan
Computer Science & Engineering
Ann Arbor, MI 48109-2121
Computational Human-Centered Analysis and Integration
The proper design of affective agents requires an understanding of human emotional perception.
Such an understanding provides designers with a method through which to estimate how an affective interface may be perceived given intended feature modulations.
However, human perception of naturalistic expressions is difficult to predict.
This difficulty is partially due to the mismatch between the emotional cue generation (the speaker) and cue perception (the observer)
and partially due to the presence of complex emotions, emotions that contain shades of multiple affective classes.
An understanding of the mapping between signal cue modulation and human perception can facilitate design improvements both for emotionally relevant and emotionally targeted expressions for use in human-computer and human-robot interaction. This understanding will further human-centered design, necessary for the wide-spread adoption of this affective technology.
Check out examples for emotional McGurk effect stimuli using the links below.
angry happy neutral sad
Please click here for a talk on this topic, presented at the Data Mining Workshop in 2013.