A Blueprint for Affective Computing

• Focuses on a topic at the frontiers of cognitive and computer science, presenting fascinating insights into how we can design computer systems that can communicate and recognise emotional states
• Bringing together specialists from psychology, philosophy, AI, and neuroscience, the book therefore represents the first attempt to ground affective computing back within the disciplines in which it was first proposed
• Written to be accessible to those in the fields of psychology, computer science, human computer interaction, and neuroscience

Readership: Students and researchers in psychology, human computer interaction, computer science, artificial intelligence

Klaus R. Scherer, Director of the Swiss Centre for Affective Sciences, University of Geneva, Switzerland, Tanja Bänziger, Gävle University, Sweden, and the Swiss Centre for Affective Sciences, University of Geneva, Switzerland, and Etienne Roesch, Centre for Integrative Neuroscience and Neurodynamics, University of Reading, United-Kingdom

Scherer, KR, Bänziger, T, Roesch E.B.: Preface
Theoretical approaches to the study of emotion in humans and machines
Introduction
1.1: Scherer, K.R.: Emotion and emotional competence: conceptual and theoretical issues for modeling
1.2: Marsella, S., Gratch, J., Petta, P.: Computational models of emotion
The emotion process: Perspectives from psychology and the neurosciences
Introduction
2.1: Scherer, KR: The component process model: a blueprint for a comprehensive computational model of emotion
2.2: Grandjean D., Sander, D.: The emotional brain meets affective computing
2.3: Bänziger, T, With, S., Kaiser, S: The face and voice of emotions: the expressions of emotions
2.4: Kreibig, S., Schaefer, G., Brosch, T.: Psychological response patterning in emotion: implications for affective computing
2.5: Parkinson, B: Emotions in interpersonal interactions
Emotional expression: Ground truth and agent evaluation
Introduction
3.1: Cowie, R., Douglas-Cowie, E., Martin, J.-C-, Devillers, L.: The essential role of human databases for learning in and validation of affectively competent agents
3.2: Scherer, KR. & Bänziger, T.: On the use of actor portrayals in research on emotional expression
Approaches to the computational modelling of emotion
Introduction
4.1: Becker-Asano, C., Wachsmuth, I.: WASABI as a case study of how misattribution of emotion can be modelled computationally
4.2: Roesch, EB, Korsten, N, Fragopanagos, N., Taylor, JG: Emotions in artificial neural networks
Approaches to the implementation of emotionally competent agents
Introduction
5.1: Hyniewska, S., Niewiadomski, R., Mancini, M., Pelachaud, C.: Expression of affects in Embodied Conversational Agents
5.2: Schröder, M., Burkhardt, F., Krstulovic, S.: Synthesis of emotional speech
5.3: Devillers, L., Vidrascu, L., Layachi, O.: Automatic detection of emotion from vocal expression
5.4: Castellano, G., Caridakis, G., Camurri, A., Karpouzis, K., Volpe, G., Kollias, S.: Body gesture and facial expression analysis for automatic affect recognition
5.5: Niewiadomski, R., Mancini, M., Hyniewska, S., Pelachaud, C.: Communicating emotional states with the Greta agent
Approaches to developing expression corpora and databases
Introduction
6.1: Bänziger, T & Scherer, KR: Introducing the Geneva Multimodal Emotion Portrayal (GEMEP) corpus
6.2: Cowie, R., Douglas-Cowie, E., Sneddon, I., McRorie, Hanratty, J., McMahon, E. ,McKeown, G.: Induction techniques developed to illuminate relationships between signs of emotion and their context, physical and social.
Conclusions