Affective computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects. It is an interdisciplinary field spanning computer science, psychology, and cognitive science. While some core ideas in the field may be traced as far back as to early philosophical inquiries into emotion, the modern idea originated with Rosalind Picard's 1995 paper entitled Affective Computing and her 1997 book of the same name published by MIT Press. One motivation for researching affective computing is the ability to give machines emotional intelligence, including simulating empathy, so that a machine can interpret the emotional state of humans and adapt its behavior to those emotions, responding appropriately.
Facts
Core ConcernBuilding systems and devices that can recognize, interpret and simulate human emotional states. 1 Connections
Associated With
Affective computing grew out of Picard's own human-computer interaction research.
Source Affective Computing (Wikipedia)
Source Affective Computing (Wikipedia)
Rosalind Picard's 1995 paper and 1997 book originated the modern field of affective computing.
Source Affective Computing (Wikipedia)
Sources
1. Affective Computing (Wikipedia)
Wikimedia FoundationLead paragraph, third sentence
the modern idea originated with Rosalind Picard's 1995 paper entitled "Affective Computing" and her 1997 book of the same name published by MIT Press.
Lead paragraph, first sentence
Affective computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects.
Associated With: Rosalind Picard, Introduction section
the modern idea originated with Rosalind Picard's 1995 paper entitled "Affective Computing" and her 1997 book of the same name
Associated With: Human Computer Interaction, Introduction/Cognitivist approaches section
Picard's focus is human-computer interaction, and her goal for affective computing is to "give computers the ability to recognize, express, and in some cases, 'have' emotions".
Associated With: Pattern Recognition, Emotional speech processing section, first sentence
Vocal parameters and prosodic features such as pitch variables and speech rate can be analyzed through pattern recognition techniques.
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