The Affective Computing Approach to Affect Measurement Journal Article uri icon

Overview

abstract

  • Affective computing (AC) adopts a computational approach to study affect. We highlight the AC approach towards automated affect measures that jointly model machine-readable physiological/behavioral signals with affect estimates as reported by humans or experimentally elicited. We describe the conceptual and computational foundations of the approach followed by two case studies: one on discrimination between genuine and faked expressions of pain in the lab, and the second on measuring nonbasic affect in the wild. We discuss applications of the measures, analyze measurement accuracy and generalizability, and highlight advances afforded by computational tipping points, such as big data, wearable sensing, crowdsourcing, and deep learning. We conclude by advocating for increasing synergies between AC and affective science and offer suggestions toward that direction.

publication date

  • April 1, 2018

has restriction

  • bronze

Date in CU Experts

  • January 28, 2019 10:47 AM

Full Author List

  • D’Mello S; Kappas A; Gratch J

author count

  • 3

Other Profiles

International Standard Serial Number (ISSN)

  • 1754-0739

Electronic International Standard Serial Number (EISSN)

  • 1754-0747

Additional Document Info

start page

  • 174

end page

  • 183

volume

  • 10

issue

  • 2