Affective Computing Ana Paiva & João Dias. Lecture 1. Course Presentation

Transcription

1 Affective Computing Ana Paiva & João Dias Lecture 1. Course Presentation

2 Motivation. What is Affective Computing? Applications and Problems Perspectives on Emotions History of Affective Sciences Communication of Emotions Emotions and Neuroscience Appraisal Theories The Affective Computer Architecture and components Recognising Emotions and other Affective states Facial and Gesture Recognition Physiological signals Speech recognition Syllabus (1)

3 Syllabus (2) Emotion Synthesis Emotion Architectures Learning and Emotion in social agents The expression of emotions in computers and robots Expression of emotion through different modalities (speech, natural language, lights, movements, etc) Expression of emotion in virtual humans Expression of emotion in social robots Applications Entertainment Educational Technology Advertising Social Media

4 Bibliography Affective Computing, Rosalind Picard, MIT Press, 1997 Understanding Emotions, K. Oatley, D. Keltner & J. Jenkins, Blackwell Publishing, 2006 The Oxford Handbook of Affective Computing, Edited by Rafael Calvo, Sidney D'Mello, Jonathan Gratch, and Arvid Kappas, 2014.

5 Evaluation Preparation, discussion, summaries and presentation of specific topics during the course (30%) Project on Affective Computing (70%)

6 Affective Computing Computing (rational) Affect (non rational) Affective Computing: a contradiction?

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8 Motivation In Artificial Intelligence: In 1967 Herb Simon emphasised that a general theory of thinking and problem solving needs to consider and incorporate the influences of emotion. In HCI: The communication with the machines needs to take into account the affective state of the user (captured by his/her voice, facial expressions, and other signals) In HCI and AI: the expression of computers when interacting with users must be natural and inspired in the way humans communicate, thus emotions should be present in such communication.

9 Emotion and Affect What are emotions? What causes them? Why do we have them?

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15 Origins

16 The Limbic System is the seat of emotion, memory and attention. It helps determine valence (if you feel positive or negative) and salience (what gets the attention). (Picard, 1997) The Limbic System

17 LeDoux findings show that the audio cortex is not always needed for auditory conditioning The amygdala is where the learning for fear conditioning occurs. There are substantially more connections from the limbic system to the cortex than vice versa. Not only can the limbic system hijack the cortex, but the limbic system influence may actually be the greater of the two. The Limbic System

18 Decision Making and Emotions Rational thinking requires participation from emotion- mediating parts of the brain. The importance of Emotional Inteligence as the ability to monitor one s own and others feeling and emotions, to descriminate among them and to use this information to guide one s thinking and action (Gardner).

19 Affective Communication Basic affect recognition and expression are expected by humans in communication So far, computer-based communication is affect-blind, affect-deaf, and generaly speaking affect-impaird.

20 What is Affective Computing? Computing that relates to, arises from, or deliberately influences emotions Rosalind Picard, 1997

21 What is and What is Not Affective Computing?

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23 Affective Sensing 23

24 Affective Processing

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26 Affective Behaviour and Expressions

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28 A quantum leap in communication will occur when computers become able to at least recognise and express affect.

29 Next lectures: Part 1 on Emotion Introduction to Affective Computing. Inspiration, main questions. Approaches to understand emotions. Emotion: evolution of emotions and cultural understanding of emotions Emotions: the body and the brain. Communication of emotions in humans and other animals Emotion and cognition. Appraisal theories

30 Next lectures: Part 1I on Computational systems Emotion Recognition. Signals and Systems. Recognition through voice and natural language Emotion Recognition through facial expression and gestures. Learned models. Emotion Synthesis: Approaisal based architectures. Emotion Synthesis: biological inspired and emotion learning. Emotion expression in agents and robots.

31 Next lectures: Part III on Entertainment Educational Technology Advertising Social Media Applications