Transactions on Affective Computing
IEEE Transactions on Affective Computing (TAC) is intended to be a cross disciplinary and international archive journal aimed at disseminating results of research on the design of systems that can recognize, interpret, and simulate human emotions and related affective phenomena. Read the full scope of TAC
Expand your horizons with Colloquium, a monthly survey of abstracts from all CS transactions!
From the April-June 2018 issue
ASCERTAIN: Emotion and Personality Recognition Using Commercial Sensors
By Ramanathan Subramanian, Julia Wache, Mojtaba Khomami Abadi, Radu L. Vieriu, Stefan Winkler, and Nicu Sebe
We present ASCERTAIN—a multimodal databaASe for impliCit pERsonaliTy and Affect recognitIoN using commercial physiological sensors. To our knowledge, ASCERTAIN is the first database to connect personality traits and emotional states via physiological responses. ASCERTAIN contains big-five personality scales and emotional self-ratings of 58 users along with their Electroencephalogram (EEG), Electrocardiogram (ECG), Galvanic Skin Response (GSR) and facial activity data, recorded using off-the-shelf sensors while viewing affective movie clips. We first examine relationships between users’ affective ratings and personality scales in the context of prior observations, and then study linear and non-linear physiological correlates of emotion and personality. Our analysis suggests that the emotion-personality relationship is better captured by non-linear rather than linear statistics. We finally attempt binary emotion and personality trait recognition using physiological features. Experimental results cumulatively confirm that personality differences are better revealed while comparing user responses to emotionally homogeneous videos, and above-chance recognition is achieved for both affective and personality dimensions.
View the PDF of this article 
View this issue in the digital library
Editorials and Announcements
Announcements
- According to Clarivate Analytics' 2016 Journal Citation Report, TAC has an impact factor of 3.149.
- Heartfelt congratulations are offered to Georgios N. Yannakakis and Julian Togelius, authors of "Experience-Driven Procedural Content Generation," who were presented with TAC's Most Influential Paper Award by Editor-in-Chief Björn W. Schuller at the 2015 6th AAAC Affective Computing and Intelligent Interaction Conference in Xi'An, P.R. China on 22 September 2015.
Editorials
- Editorial: Transactions on Affective Computing – Good Reasons for Joy and Excitement (Jan-March 2018)
- Editorial: IEEE Transactions on Affective Computing – Challenges and Chances (Jan-March 2017)
- Editorial: Transactions on Affective Computing – Changes and Continuance (Jan-March 2016)
- Editorial: State of the Journal (July-Sept 2014)
- Introduction to TAC by J. Gratch
Guest Editorials
- Towards Machines Able to Deal with Laughter (Oct-Dec 2017)
- Toward Commercial Applications of Affective Computing (April-June 2017)
- Best of Bodynets 2014: Editorial (July-Sept 2016)
- Challenges and Perspectives for Affective Analysis in Multimedia (July-Sept 2015)
- Introduction to the "Best of ACII 2013" Special Section (April-June 2015)
- Affect and Wellbeing: Introduction to Special Section (July-Sept 2014)
- Editorial for the Special Section on Ethics and Affective Computing
- Introduction to the Affect-Based Human Behavior Understanding Special Issue
- Affective Computing: From Laughter to IEEE by R.W. Picard
Reviewers List
Author Index
Access recently published TAC articles
Subscribe to the RSS feed of recently published TAC content
Sign up for e-mail notifications through IEEE Xplore Content Alerts
View TAC preprints in the Computer Society Digital Library
View the PDF of TAC's ongoing call-for-papers.
TAC is indexed in ISI