Machines outperform laypersons in recognizing emotions elicited by autobiographical recollection
Number of pages
SourceHuman-Computer Interaction, 28, 6, (2013), pp. 479-517
Article / Letter to editor
Display more detailsDisplay less details
SW OZ DCC AI
SubjectCognitive artificial intelligence; DI-BCB_DCC_Theme 2: Perception, Action and Control
Over the last decade, an increasing number of studies have focused on automated recognition of human emotions by machines. However, performances of machine emotion recognition studies are difficult to interpret because benchmarks have not been established. To provide such a benchmark, we compared machine with human emotion recognition. We gathered facial expressions, speech, and physiological signals from 17 individuals expressing 5 different emotional states. Support vector machines achieved an 82% recognition accuracy based on physiological and facial features. In experiments with 75 humans on the same data, a maximum recognition accuracy of 62.8% was obtained. As machines outperformed humans, automated emotion recognition might be ready to be tested in more practical applications.
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.