Affective computing is the study of how emotions can have a major impact within intelligent interactive computer systems. Emotions are known to be central and basic to human interaction. Affective computing researchers attempt to bring emotions into artificial systems that interact with humans. Research in this area focusses on four primary areas. First, the study of basic theories of emotion, from psychological, sociological, and neuroscientific perspectives. Second, the study of techniques to recognise emotion from psysiological signals including speech, heartrate, skin conductance, eye gaze and body posture. Third, the study of how to generate believable emotional signals in virtual agents, including embodied conversational agents, avatars, assistive agents, and chatbots. Fourth, the study of how to implement theories of emotion in particular domains, and how to integrate recognition and generation of affect to make more efficent, believable, enjoyable and useful intelligent interactive systems.
See also a video description of the class
- All communication should take place using the
Slack group. You will receive an invitation to sign up in the first week of class.
- Public Slack posts are the preferred method for questions about course material, etc. Students can then help each other and instructors can read/reply.
- You can also send me email with personal questions
- See Full Schedule for a detailed list of readings for each lecture
- February 2nd Project proposals due.
- February 28th Assignment 1 due (PDF here)
- March 30th Assignment 2 due
- April 14th Project reports due
The course will be a combination of lectures by the instructor or guests, and
student-led presentation and discussion of recent research papers.
With the research papers, students will be responsible for presenting them in class and
The grading breakdown is subject to change.
- Student presentations (20%)
- Assignments (2 x 10% = 20%)
- Individual project (50%) see here for details
The last 10% will be allocated for overall course participation. Group projects may be OK by permission from instructor.
The course will be relevant to researchers in human-computer interaction and in artificial intelligence.
There are no formal pre-requisites, as the field is inherently multi-disciplinary and requires breadth
across disciplines including AI, sociology and psychology. Some of the topics involve some mathematics,
but the students will be given the necessary background during the course. The ideal project is one that
will show how affective reasoning can be used in the student's research, regardless of the major area.
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: A student who believes that a decision affecting
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Avoiding Academic Offenses
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line between acceptable and unacceptable academic behaviour,
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Faculty of Mathematics Cheating and Student Academic Discipline
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