Affective Computing

What is Affective Computing?

Affective Computing is a multidisciplinary field that involves the study and development of systems that can recognize, interpret, and simulate human emotions and affective states. It aims to bridge the gap between human emotions and computing systems, enabling machines to better understand, adapt to, and interact with their users. Affective computing has applications in various domains, such as healthcare, education, entertainment, and human-computer interaction.

What are the main components of Affective Computing?

Affective computing typically involves the following components:

  1. Emotion recognition: The process of identifying human emotions from various sources, such as facial expressions, speech, physiological signals, or text.

  2. Emotion modeling: The representation of emotions and affective states in a computationally tractable form, often using dimensional or categorical models.

  3. Emotion synthesis: The generation of artificial emotions, which can be expressed through avatars, robots, or other artificial agents to enhance human-computer interaction.

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