Multimodal detection of affective states: A roadmap through diverse technologies

Javier Gonzalez-Sanchez, Winslow Burleson, Maria E. Chavez-Echeagaray, Robert Atkinson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

One important way for systems to adapt to their individual users is related to their ability to show empathy. Being empathetic implies that the computer is able to recognize a user's affective states and understand the implication of those states. Detection of affective states is a step forward to provide machines with the necessary intelligence to appropriately interact with humans. This course provides a description and demonstration of tools and methodologies for automatically detecting affective states with a multimodal approach.

Original languageEnglish (US)
Title of host publicationCHI EA 2014
Subtitle of host publicationOne of a ChiNd - Extended Abstracts, 32nd Annual ACM Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
Pages1023-1024
Number of pages2
ISBN (Print)9781450324748
DOIs
StatePublished - Jan 1 2014
Event32nd Annual ACM Conference on Human Factors in Computing Systems, CHI EA 2014 - Toronto, ON, Canada
Duration: Apr 26 2014May 1 2014

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Other

Other32nd Annual ACM Conference on Human Factors in Computing Systems, CHI EA 2014
CountryCanada
CityToronto, ON
Period4/26/145/1/14

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Keywords

  • Affect-driven adaptation
  • Affective states
  • Emotion recognition
  • Multimodal
  • Sensors

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

Cite this

Gonzalez-Sanchez, J., Burleson, W., Chavez-Echeagaray, M. E., & Atkinson, R. (2014). Multimodal detection of affective states: A roadmap through diverse technologies. In CHI EA 2014: One of a ChiNd - Extended Abstracts, 32nd Annual ACM Conference on Human Factors in Computing Systems (pp. 1023-1024). (Conference on Human Factors in Computing Systems - Proceedings). Association for Computing Machinery. https://doi.org/10.1145/2559206.2567820