Affective Computing is an interdisciplinary field that involves Computer Science, Psychology, and Cognitive Science.
Designing affective computing systems aims to simulate and recognize emotions like humans. It can also be considered a part of emotional Intelligence, a subset of Artificial Intelligence. The best example is the new Apple Watch Ultra which uses sensors to detect body temperature, skin temperature, and other psychological data through its sensors and communicate it to AI systems for health analysis.
Affective Computing is an emerging field that is placed at the intersection of artificial Intelligence and behavioural science. Affective Computing involves studying and developing systems that recognize, interpret, process and simulate human emotions. It has recently seen significant advances from exploratory studies to real-world applications. Multimodal Affective Computing offers readers a concise overview of the state-of-the-art and emerging themes in affective computing, including a comprehensive review of the existing approaches in applied affective computing systems and social signal processing. It covers Affective facial expression recognition, affective body expression, affective speech processing, affective text, and dialogue processing. Moreover, it covers computational models of emotion, theoretical foundations, and affective speech and music processing.
This book identifies future directions for affective computing and summarizes guidelines for developing next-generation
Affective computing systems that are effective, safe, and human-centred. The book is an informative resource for
Academicians, professionals, researchers, and students at engineering and medical institutions working in the areas of
Applied Affective computing, sentiment analysis, and emotion recognition.