1. Survey of Affective Computing for Digital Home
Tsai-Yen Li
Computer Science Department
National Chengchi University

2. Outline Affective computing overview Research activities
Issues and approaches
Applications in digital home
Research challenges

3. Definition of Affective Computing
Affective computing: computing that relates to, arises from, or deliberately influences emotions
Multidiscipline across several academic fields: such as computer science, cognitive science, psychology, neuroscience, etc.
Multidiscipline inside Computer Science: machine learning, pattern recognition, signal processing, computer vision, speech analysis, computer animation, and protocol design.

4. Issues in Affective Computing
Emotion perception
Emotion modeling
Emotion expression
Emotion communication

5. Research Groups on Emotion
United Stats:
Affective Computing (M.I.T.), OZ (C.M.U.), Joe LeDoux's Laboratory (N.Y.U.), Responsive Virtual Human Technology (RTI), Affect Analysis Group (U. Pittsburgh), etc.
United Kingdom:
U. of Cambridge, U. of Birmingham, U. of York, etc.
Others:
Switzerland, Finland, Netherlands, Canada, Austria, etc.

6. Emotion Perception Verbal: Non-verbal: Voice: magnitude, pitch, etc.
Dialog: limited vocabulary
Non-verbal:
Facial: feature-based, appearance-based
Physiological symptoms: wearable computer
heart rate variability, brainwaves, respiration, muscle tension, blood pressure and temperature
Input behaviors: emotional mouse
Gestures

7. Computational Models of Affect
Architecture-level models
Mostly based on the OCC model.
How emotions interact with other components such as goal, preference, stimulus, etc.
Task-level models
enhancing system performance on a particular problem-solving task such as NLP, Military applications.
Mechanism-level models
To emulate high-level or low-level aspects of the mechanism involved in emotional processing
關於情緒方面在心裡學上的分類

8. OCC Model

9. Research Groups on Emotional Virtual Human
Center for Human Modeling and Simulation, UPenn: by Norman Badler
Kinematics, dynamics, NLP
Virtual Reality Lab, EPFL, Switzerland : by Daniel Thalmann
Motion, crowd, virtual environment
Miralab, Switzerland: by Nadia Magnenat-Thalmann
Facial, cloth, skin

10. Emotion Expression Emotion mechanism (Oliverira 2003):
Appraisal: OCC model
Copping: expression
Expression types:
Verbal: speech, text
Non-verbal: facial expression, motion, gesture, actions, etc.

11. Emotion Modeling and Expression Language
PAR (Parameterized Action Representation )
Badler2000, representation lang.
CML (Character Markup Language)
Arafa2003, scripting and representation lang., XML
AML (Avatar Markup Language)
Thalmann2002, scripting lang., XML, emotion
VHML (Virtual Human Markup Language)
Marriott2002, scripting and representation lang.
HML (Human Markup Language):
representation lang., XML
APML (Affective Presentation Markup Language):
scripting and representation lang., XML, emotion

12. Application in Digital Home
Levels of applications
Expression only: Mac, Office agent
Perception only: intelligent tutoring system
Perception and expression: David in AI
Applications in digital home:
Entertainment: emotional virtual characters
Instructional: context-aware virtual presenter
Environmental setting: temperature, light, decoration, emergent alert, etc.
Education: intelligent tutor/nanny
Ingredients for other home applications

13. Research Challenges
Are these results recognized people’s emotions accuracy?
Does it need to be accurate? (joy, anger)
Could the data collected in laboratories be placed a digital home ?
Analogy of computer vision.
Ethics issue
Consider at as low level as possible.
Other technical challenges
Distinguishability, Naturalness, etc.