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Guest Editors:

  • Björn W. Schuller, Imperial College London, UK and University of Augsburg, Germany
  • Matti Pietikäinen, University of Oulu, Finland


The history of Affective Computing spans roughly 25 years, with roots reaching even earlier in time in areas such as facial expression recognition or emotional speech analysis and synthesis. As a field, it has been one of the earliest adopters of deep learning and is by nature massively multimodal, spanning from audio over text, images, video, physiological to haptical and further data. At the same time, it ranges from analysis to synthesis and depends heavily on signal processing and machine learning. It is also interdisciplinary in nature, with work being done in computer science and engineering to psychology, philosophy, medicine, and even disciplines such as linguistics, musicology, or the arts. In fact, it concerns all of us, as it is all about emotions –and, emotions are all about life, arts, being.

This special issue will bring together leading experts in the field of Affective Computing to provide a much needed all-encompassing snapshot of the field. The issue will provide a holistic tutorial and overview, ranging from analysis to synthesis and data to applications, for the interested non-specialists as well as experts in the field.

Publication Date: 2023