Intelligent Signal Processing for Affective Computing

Affective computing is computing that relates to, arises from, or deliberately influences emotion or other affective phenomena. Human emotion and affect in general are fundamental to human experience, influencing cognition, perception, and everyday tasks such as learning and communication, but are also fundamental to human health and well-being. The field of affective computing has matured over its roughly two-and-a-half decades coming closer than ever to the point of usage at scale. Affective computing is facing a plethora of different signal types - audio, video, and physiological signals, to name but the most dominant.

Affective computing is computing that relates to, arises from, or deliberately influences emotion or other affective phenomena. Human emotion and affect in general are fundamental to human experience, influencing cognition, perception, and everyday tasks such as learning and communication, but are also fundamental to human health and well-being. The field of affective computing has matured over its roughly two-and-a-half decades coming closer than ever to the point of usage at scale. Affective computing is facing a plethora of different signal types—audio, video, and physiological signals, to name but the most dominant.

In everyday usage, affective computing has the potential to massively change how we interact with computing and robotic devices: they will be able to respond more appropriately to our emotions and moods, and able to show signs of empathy through mimicry, but may also use affective information for retrieval or their own creativity. Affective computing becoming truly robust also has the potential to change mental health care radically, once computing systems enable monitoring our health and well-being, detect early signs of depression, and/or identify signs of neurodevelopmental conditions (e.g., diagnosis of autism in children to burnout prevention), among others.