Summer 2020 - CMPT 983 G100

Special Topics in Artificial Intelligence (3)

Affective Computing

Class Number: 4156

Delivery Method: In Person

Overview

  • Course Times + Location:

    Tu 2:30 PM – 4:20 PM
    REMOTE LEARNING, Burnaby

    Th 2:30 PM – 3:20 PM
    REMOTE LEARNING, Burnaby

  • Exam Times + Location:

    Aug 21, 2020
    12:00 PM – 3:00 PM
    Location: TBA

Description

COURSE DETAILS:

Emotions play a central role in our daily lives as humans. The field of affective computing studies how emotions can have a major impact in the construction of interactive, intelligent agents and interfaces. This course will cover topics in affective computing as follows. First, theories and models of emotion (including core affect, mood, feelings) from psychological, neuroscientific and computational perspectives will be reviewed. Secondly, we will study techniques for automatic perception of human internal state, including using machine learning to understand sentiment using modalities such as gaze, posture, speech, text, movement and music. Thirdly, synthesis and expression of emotion and empathy in virtual agents, robots, chatbots and synthetic characters will be explored. Finally, we will delve into the implementation of emotion theories, including how to use the above techniques to make more believable, effective, enjoyable, and useful intelligent interactive systems.
Note: Students will need access to a computer and internet to complete this course. Two 50-minute lectures will be delivered in real-time via BBCollaborate Ultra during scheduled lecture hours. Recordings of lectures will be posted after each class. Online activities will replace one hour of lecture per week, and participation in online discussions will contribute toward the final mark.

Written work for this course will be submitted via Turnitin, a third-party service licensed for use by SFU. Turnitin is used for originality checking to help detect plagiarism. Students will be required to create an account with Turnitin, and to submit their work via that account, on the terms stipulated in the agreement between the student and Turnitin. This agreement includes the retention of your submitted work as part of the Turnitin database. Any student with a concern about using the Turnitin service may opt to use an anonymous identity in their interactions with Turnitin. Students who do not intend to use Turnitin in the standard manner must notify the instructor at least two weeks in advance of any submission deadline. In particular, it is the responsibility of any student using the anonymous option (i.e., false name and temporary email address created for the purpose) to inform the instructor such that the instructor can match up the anonymous identity with the student.

Topics

  • Psychological theories of emotion
  • Neuroscientific perspectives of emotion
  • Physiology of emotion
  • Computational models of affect
  • Robots / agents that "have" emotion
  • Multimodal affect recognition
  • Expression of emotion by robots/agents / synthetic characters
  • Social signal processing
  • Speech/sound processing and synthesis
  • Visual processing of human behaviour
  • Affect detection in text
  • Affect elicitation and user studies
  • Machine empathy
  • Ethical implications of affective computing
  • Applications in socially interactive systems

Grading

NOTES:

The course grade will be based on assignments, a final project and exam (TBC).

Materials

RECOMMENDED READING:

 

  • Affective Computing
  • Picard, R. W.
  • MIT PRESS
  • 2000

ISBN: 9780262661157

  • The Oxford Handbook of Affective Computing
  • Calvo, R. A., S. K. D'Mello, J. Gratch, et al
  • Oxford University Press
  • 2014

ISBN: 9780199942237

Graduate Studies Notes:

Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html

TEACHING AT SFU IN SUMMER 2020

Please note that all teaching at SFU in summer term 2020 will be conducted through remote methods. Enrollment in this course acknowledges that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes.

Students with hidden or visible disabilities who believe they may need class or exam accommodations, including in the current context of remote learning, are encouraged to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 778-782-3112) as soon as possible to ensure that they are eligible and that approved accommodations and services are implemented in a timely fashion.