ABOUT THE COURSE: Affective Computing focuses on enabling the machines with emotion recognition and adaptive interaction. It lies in the intersection of Computer Science, design and human psychology. This course will overview the emotion theory, computational modelling of emotions, analysis of emotions using different modalities (such as voice, facial expressions, physiological signals etc) and related machine learning and/or signal processing techniques. We will also discuss ethical, legal and social implications of affective computing particularly in relation to Human-Machine Interaction.INTENDED AUDIENCE: Senior UG and PG Students PREREQUISITES: Mandatory Prerequisites: 1.Programming 2.Artificial Intelligence 3.Machine LearningDesirable Prerequisites: 4.Human-Computer Interaction 5.Deep LearningINDUSTRY SUPPORT: In general, any company industry working with AI/ML will recognize this course. Some examples include: 1.Amazon 2.Apple 3.Google 4.Meta 5.Microsoft
Overview
Syllabus
Week 1: Fundamentals of Affective Computing
Week 2:Emotion Theory and Emotional Design
Week 3:Experimental Design: Affect Elicitation; Research and Development Tools
Week 4:Emotions in Voice
Week 5:Emotions in Facial Expressions
Week 6:Emotions in Text
Week 7:Emotions in Physiological Signals
Week 8:Multimodal Emotion Recognition
Week 9:Emotional Empathy in Agents/Machines/Robots
Week 10:Online and Adaptive Recognition of Emotions: Challenges and Opportunities
Week 11:Case Study: Updated from Time to Time
Week 12:Ethical Issues: Ethical, legal and Social Implications of Affective Computing
Taught by
Prof. Jainendra Shukla, Prof. Abhinav Dhall
