'Affective computing' is a branch of computing concerned with the theory and construction of machines which can detect, respond to, and simulate human emotional states. This book presents an interdisciplinary exploration of this rapidly expanding field, aimed at those in psychology, computational neuroscience, computer science, and AI.
"The Oxford Handbook of Affective Computing is a definitive reference in the burgeoning field of affective computing (AC), a multidisciplinary field encompassing computer science, engineering, psychology, education, neuroscience, and other disciplines. AC research explores how affective factors influence interactions between humans and technology, how affect sensing and affect generation techniques can inform our understanding of human affect, and on the design, implementation, and evaluation of systems involving affect at their core. The volume features 41 chapters and is divided into five sections: history and theory, detection, generation, methodologies, and applications. Section 1 begins with the making of AC and a historical review of the science of emotion. The following chapters discuss the theoretical underpinnings of AC from an interdisciplinary viewpoint. Section 2 examines affect detection or recognition, a commonly investigated area. Section 3 focuses on aspects of affect generation, including the synthesis of emotion and its expression via facial features, speech, postures, and gestures. Cultural issues are also discussed. Section 4 focuses on methodological issues in AC research, including data collection techniques, multimodal affect databases, formats for the representation of emotion, crowdsourcing techniques, machine learning approaches, affect elicitation techniques, useful AC tools, and ethical issues. Finally, Section 5 highlights applications of AC in such domains as formal and informal learning, games, robotics, virtual reality, autism research, health care, cyberpsychology, music, deception, reflective writing, and cyberpsychology. This compendium will prove suitable for use as a textbook and serve as a valuable resource for everyone with an interest in AC."--
"'Affective computing' is a branch of computing concerned with the theory and construction of machines which can detect, respond to, and simulate human emotional states. It is an interdisciplinary field spanning the computer sciences, psychology, and cognitive science. Affective computing is a rapidly developing field within industry and science. There is now a great drive to make technologies such as robotic systems, avatars in service-related human computer interaction, e-learning, game characters, or companion devices more marketable by endowing the 'soulless' robots or agents with the ability to recognize and adjust to the user's feelings as well as to be able to communicate appropriate emotional signals. A Blueprint for Affective Computing: A sourcebook and manual is the very first attempt to ground affective computing within the disciplines of psychology, affective neuroscience, and philosophy. This book illustrates the contributions of each of these disciplines to the development of the ever-growing field of affective computing. In addition, it demonstrates practical examples of cross-fertilization between disciplines in order to highlight the need for integration of computer science, engineering and the affective sciences. Focusing on a topic at the frontiers of human computer interaction research, this book will be of great interest to students and researchers in psychology, neuroscience, computational neuroscience, computer science, and artificial intelligence"--
Recent years have seen the rise of a remarkable partnership between the social and computational sciences on the phenomena of emotions. This book reports on the state-of-the-art in both social science theory and computational methods, and illustrates how these two fields, together, can both facilitate practical computer/robotic applications and illuminate human social processes.
Neuroscientific research on emotion has developed dramatically over the past decade. The cognitive neuroscience of human emotion, which has emerged as the new and thriving area of 'affective neuroscience', is rapidly rendering existing overviews of the field obsolete. This handbook provides a comprehensive, up-to-date and authoritative survey of knowledge and topics investigated in this cutting-edge field. It covers a range of topics, from face and voice perception to pain and music, as well as social behaviors and decision making. The book considers and interrogates multiple research methods, among them brain imaging and physiology measurements, as well as methods used to evaluate behavior and genetics. Editors Jorge Armony and Patrik Vuilleumier have enlisted well-known and active researchers from more than twenty institutions across three continents, bringing geographic as well as methodological breadth to the collection. This timely volume will become a key reference work for researchers and students in the growing field of neuroscience.
This book constitutes refereed proceedings of the COST 2102 International Training School on Cognitive Behavioural Systems held in Dresden, Germany, in February 2011. The 39 revised full papers presented were carefully reviewed and selected from various submissions. The volume presents new and original research results in the field of human-machine interaction inspired by cognitive behavioural human-human interaction features. The themes covered are on cognitive and computational social information processing, emotional and social believable Human-Computer Interaction (HCI) systems, behavioural and contextual analysis of interaction, embodiment, perception, linguistics, semantics and sentiment analysis in dialogues and interactions, algorithmic and computational issues for the automatic recognition and synthesis of emotional states.
During the past decade, emotional intelligence has been subjected to both scientific and public scrutiny. Numerous articles have been published on the topic in both academic journals and the popular press, testifying to the potential usefulness of emotional intelligence in psychology, business, education, the home, and the workplace. However, until now, there has been no systematic synthesis that grounds emotional intelligence in contemporary theory, while simultaneously sorting scientific approaches from popular fads and pseudoscience. Bringing together leading international experts from a variety of sub-disciplines, this volume aims to integrate recent research on emotional intelligence. The contributors address a set of focused questions concerning theory, measures, and applications: How does emotional intelligence relate to personality? What is the optimal approach to testing emotional intelligence? How can emotional intelligence be trained? In the final section of the book, the volume editors distill and synthesize the main points made by these experts and set forth an agenda for building a science of emotional intelligence in the future. Science of Emotional Intelligence will be an invaluable resource for researchers and professionals in psychology, education, the health sciences, and business.
Few areas have witnessed the type of growth we have seen in the affective sciences in the past decades. Across psychology, philosophy, economics, and neuroscience, there has been an explosion of interest in the topic of emotion and affect. Comprehensive, authoritative, up-to-date, and easy-to-use, the new Oxford Companion to Emotion and the Affective Sciences is an indispensable resource for all who wish to find out about theories, concepts, methods, and research findings in this rapidly growing interdisciplinary field - one that brings together, amongst others, psychologists, neuroscientists, social scientists, philosophers, and historians. Organized by alphabetical entries, and presenting brief definitions, concise overviews, and encyclopaedic articles (all with extensive references to relevant publications), this Companion lends itself to casual browsing by non-specialists interested in the fascinating phenomena of emotions, moods, affect disorders, and personality as well as to focused search for pertinent information by students and established scholars in the field. Not only does the book provide entries on affective phenomena, but also on their neural underpinnings, their cognitive antecedents and the associated responses in physiological systems, facial, vocal, and bodily expressions, and action tendencies. Numerous entries also consider the role of emotion in society and social behavior, as well as in cognitive processes such as those critical for perception, attention, memory, judgement and decision-making. The volume has been edited by a group of internationally leading authorities in the respective disciplines consisting of two editors (David Sander and Klaus Scherer) as well as group of 11 associate editors (John T. Cacioppo, Tim Dalgleish, Robert Dantzer, Richard J. Davidson, Ronald B. de Sousa, Phoebe C. Ellsworth, Nico Frijda, George Loewenstein, Paula M. Niedenthal, Peter Salovey, and Richard A. Shweder). The members of the editorial board have commissioned and reviewed contributions from major experts on specific topics. In addition to comprehensive coverage of technical terms and fundamental issues, the volume also highlights current debates that inform the ongoing research process. In addition, the Companion contains a wealth of material on the role of emotion in applied domains such as economic behaviour, music and arts, work and organizational behaviour, family interactions and group dynamics, religion, law and justice, and societal change. Highly accessible and wide-ranging, this book is a vital resource for scientists, students, and professionals eager to obtain a rapid, conclusive overview on central terms and topics and anyone wanting to learn more about the mechanisms underlying the emotions dominating many aspects of our lives.
Providing a complete review of existing work in music emotion developed in psychology and engineering, Music Emotion Recognition explains how to account for the subjective nature of emotion perception in the development of automatic music emotion recognition (MER) systems. Among the first publications dedicated to automatic MER, it begins with
From the Foreword: "In this book Joscha Bach introduces Dietrich Dörner's PSI architecture and Joscha's implementation of the MicroPSI architecture. These architectures and their implementation have several lessons for other architectures and models. Most notably, the PSI architecture includes drives and thus directly addresses questions of emotional behavior. An architecture including drives helps clarify how emotions could arise. It also changes the way that the architecture works on a fundamental level, providing an architecture more suited for behaving autonomously in a simulated world. PSI includes three types of drives, physiological (e.g., hunger), social (i.e., affiliation needs), and cognitive (i.e., reduction of uncertainty and expression of competency). These drives routinely influence goal formation and knowledge selection and application. The resulting architecture generates new kinds of behaviors, including context dependent memories, socially motivated behavior, and internally motivated task switching. This architecture illustrates how emotions and physical drives can be included in an embodied cognitive architecture. The PSI architecture, while including perceptual, motor, learning, and cognitive processing components, also includes several novel knowledge representations: temporal structures, spatial memories, and several new information processing mechanisms and behaviors, including progress through types of knowledge sources when problem solving (the Rasmussen ladder), and knowledge-based hierarchical active vision. These mechanisms and representations suggest ways for making other architectures more realistic, more accurate, and easier to use. The architecture is demonstrated in the Island simulated environment. While it may look like a simple game, it was carefully designed to allow multiple tasks to be pursued and provides ways to satisfy the multiple drives. It would be useful in its own right for developing other architectures interested in multi-tasking, long-term learning, social interaction, embodied architectures, and related aspects of behavior that arise in a complex but tractable real-time environment. The resulting models are not presented as validated cognitive models, but as theoretical explorations in the space of architectures for generating behavior. The sweep of the architecture can thus be larger-it presents a new cognitive architecture attempting to provide a unified theory of cognition. It attempts to cover perhaps the largest number of phenomena to date. This is not a typical cognitive modeling work, but one that I believe that we can learn much from." --Frank E. Ritter, Series Editor Although computational models of cognition have become very popular, these models are relatively limited in their coverage of cognition-- they usually only emphasize problem solving and reasoning, or treat perception and motivation as isolated modules. The first architecture to cover cognition more broadly is PSI theory, developed by Dietrich Dorner. By integrating motivation and emotion with perception and reasoning, and including grounded neuro-symbolic representations, PSI contributes significantly to an integrated understanding of the mind. It provides a conceptual framework that highlights the relationships between perception and memory, language and mental representation, reasoning and motivation, emotion and cognition, autonomy and social behavior. It is, however, unfortunate that PSI's origin in psychology, its methodology, and its lack of documentation have limited its impact. The proposed book adapts Psi theory to cognitive science and artificial intelligence, by elucidating both its theoretical and technical frameworks, and clarifying its contribution to how we have come to understand cognition.
