Kies de Nederlandse taal
Course module: 201600073
Affective Computing
Course info
Course module201600073
Credits (ECTS)5
Course typeCourse
Language of instructionEnglish
Contact persondr. K.P. Truong
Lecturer G. Englebienne
prof.dr. D.K.J. Heylen
dr. K.P. Truong
Contactperson for the course
dr. K.P. Truong
Academic year2021
Starting block
Application procedureYou apply via OSIRIS Student
Registration using OSIRISYes
After completing this course, the student:
  • Has knowledge of the current state of the art in affective computing (AC)
  • Can conduct a study in one of the fields of affective computing
  • Has understanding of the main concepts from psychology and computer science that are relevant for the field of AC
This course provides an overview of several research areas in the field of Affective Computing. The student is introduced in the field and the current state of the art in a selected number of research areas.
The course consists of lectures discussing emotion theory, data collection and annotation, vocal and facial expression analysis, machine learning and social signal processing, and affect generation. Students will get hands-on experience in collecting data, designing, developing, and evaluating an application that can recognize and generate affective/social behavior. They will work on a project in which a research question related to Affective Computing needs to be formulated, a small dataset needs to be collected, and an analysis needs to be carried out. During lab sessions, students will get tutorials about the use of relevant tools and will be given the opportunity to ask for feedback about their project. Papers covering several topics in Affective Computing will be provided.
The assessment is based on a final written report that presents the project and a written exam that addresses the papers.
The course consists of
  • 25% Research: students will read research papers critically and will investigate and develop affective technology themselves)
  • 25% Understanding Human: students will learn about emotion theory, how humans express themselves through the voice, face and physiology, and how humans annotate affect
  • 30% Technology: students will learn to develop and evaluate an application that can recognize and generate affective/social behavior
  • 10% Design: students will design a study/application that can recognize and generate affective/social behavior
  • 10% Storytelling: students will write a final report about the study/application they developed
Participating study
Master Interaction Technology
Required materials
Recommended materials
Calvo, R. A., D'Mello, S., Gratch, J., & Kappas, A. (Eds.). (2015). The Oxford handbook of affective computing. Oxford Library of Psychology.
Instructional modes
Presence dutyYes

Presence dutyYes

Report, Exam

Kies de Nederlandse taal