AV+ EC 2015--the first affect recognition challenge bridging across audio, video, and physiological data

Ringeval, Fabien; Schuller, Bj�rn; Valstar, Michel; Jaiswal, Shashank; Marchi, Erik; Lalanne, Denis; Cowie, Roddy; Pantic, Maja

Abstract

We present the first Audio-Visual+ Emotion recognition Challenge and workshop (AV+EC 2015) aimed at comparison of multimedia processing and machine learning methods for automatic audio, visual and physiological emotion analysis. This is the 5th event in the AVEC series, but the very first Challenge that bridges across audio, video and physiological data. The goal of the Challenge is to provide a common benchmark test set for multimodal information processing and to bring together the audio, video and physiological emotion recognition communities, to compare the relative merits of the three approaches to emotion recognition under well-defined and strictly comparable conditions and establish to what extent fusion of the approaches is possible and beneficial. This paper presents the challenge, the dataset and the performance of the baseline system.

Citation

Ringeval, F., Schuller, B., Valstar, M., Jaiswal, S., Marchi, E., Lalanne, D., …Pantic, M. (2015). AV+ EC 2015--the first affect recognition challenge bridging across audio, video, and physiological data.

• Conference Name: 5th International Workshop on Audio/Visual Emotion Challenge (AVEC)
• End Date: Oct 30, 2015
• Publication Date: Jan 1, 2015
• Deposit Date: Jan 21, 2016
• Publicly Available Date: Jan 21, 2016
• Journal: Proceedings of the 5th International Workshop on Audio/Visual Emotion Challenge (AVEC), ACM MM, Brisbane, Australia
• Peer Reviewed: Peer Reviewed
• Keywords: affective computing, emotion recognition, speech, facial expression, physiological signals, challenge
• Public URL: https://nottingham-repository.worktribe.com/output/992957
• Publisher URL: http://dl.acm.org/citation.cfm?doid=2808196.2811642
• Additional Information: Published in: AVEC '15: Proceedings of the 5th International Workshop on Audio/Visual Emotion Challenge. New York : ACM, 2015. ISBN 9781450337434 p. 3-8, doi: 10.1145/2808196.2811642