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[NOTE: I will be accepting PHD students
for FALL 2020]
Research Interests
Affective Computing, Cognitive Modeling,
Human-Computer Interaction, Virtual Humans, Persuasive Technology
My research is directed toward developing
human-like software agents for virtual training environments and to use
these computational methods to concretize psychological theories of human
behavior. Specifically, I investigate how algorithms can control the
behavior of characters in virtual worlds, endowing them with an ability to
think and engage in socio-emotional interactions with human users, using both
verbal and nonverbal communication. Such methods can deepen our
understanding of human behavior, by instantiating and systematically
manipulating psychological theories. They also have wide application to
such areas as training, entertainment and clinical diagnosis, assessment
and treatment.
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Emotion Modeling
Emotions have a
pervasive impact over our lives. They shape how we perceive the world,
how we make decisions, and play a key role in social communication. In
the context of virtual training environments, emotions also play a key
role in the believability of the simulation and the extent to which a
student will feel immersed in the experience. Realizing psychological
theories as working computational models advances science by forcing
concreteness, revealing hidden assumptions, and creating dynamic
artifacts that can be subject to empirical study. These two videos give a high-level
overview of our emotion modeling research: Sweet
Emotion, CACM
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Virtual
Humans
The Virtual Human
Project brings together research in intelligent tutoring, natural
language recognition and generation, interactive narrative, emotional
modeling, and immersive graphics and audio. The focus is on creating a
highly realistic and compelling training environment. The system includes
an 8'x30' wrap-around screen, 10.2 channels of immersive audio, and
interactive synthetic humans that can interact with the trainee and
respond emotionally to their decisions. Applications of this technology
include the Mission Rehearsal Exercise [MRE Movie Clip] and the
Stability and Support Operations [SASO Movie Clip]
training prototypes.
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Social Emotions and Rapport
When
people interact their speech prosody, gesture, gaze, posture, and facial
expression contribute to establishment of a sense of rapport. Rapport is argued to underlie success in
negotiations, psychotherapeutic effectiveness, classroom performance and
even susceptibility to hypnosis.
The rapport project uses machine vision and prosody analysis to
create virtual humans that can detect and respond in real-time to human
gestures, facial expressions and emotional cues and create a sense of
rapport. These techniques have a demonstrable beneficial impact on human
interaction. [Rapport Movie Clip]
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Anthropomorphism in Human-Machine
Interaction
There is growing interest in endowing machines with more
human-like characteristics, fueled by the assumption that this will
enhance the effectiveness of human-machine interactions. Research has
demonstrated that machines can be made more human-like, but less research
has considered if this benefits or harms human-machine team performance.
Indeed, a review of the literature illustrates that human-like qualities
can results in unintended and disruptive consequences. Sometimes, getting
people to treat a computer like a human can often undermine some of the
unique advantages machines bring to human-machine teams Our
anthropomorphism aims to cast such contradictorily into an overall
framework that can inform the design of effective machines. (e.g., see this
example).
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