AVEC 2017--Real-life depression, and affect recognition workshop and challenge

Ringeval, Fabien, Schuller, Björn, Valstar, Michel, Gratch, Jonathan, Cowie, Roddy, Scherer, Stefan, Mozgai, Sharon, Cummins, Nicholas, Schmitt, Maximilian and Pantic, Maja (2017) AVEC 2017--Real-life depression, and affect recognition workshop and challenge. In: 7th Audio/Visual Emotion Challenge and Workshop, 23 October 2017, Mountain View, California, USA.

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The Audio/Visual Emotion Challenge and Workshop (AVEC 2017) “Real-life depression, and affect” will be the seventh competition event aimed at comparison of multimedia processing and machine learning methods for automatic audiovisual depression and emotion analysis, with all participants competing under strictly the same conditions. .e goal of the Challenge is to provide a common benchmark test set for multimodal information processing and to bring together the depression and emotion recognition communities, as well as the audiovisual processing communities, to compare the relative merits of the various approaches to depression and emotion recognition from real-life data. .is paper presents the novelties introduced this year, the challenge guidelines, the data used, and the performance of the baseline system on the two proposed tasks: dimensional emotion recognition (time and value-continuous), and dimensional depression estimation (value-continuous).

Item Type: Conference or Workshop Item (Paper)
RIS ID: https://nottingham-repository.worktribe.com/output/889009
Additional Information: Published in: Proceedings of the 7th International Workshop on Audio/Visual Emotion Challenge. New York : ACM, 2017, p. 3-9. doi:10.1145/3133944.3133953.
Keywords: Affective Computing; Social Signal Processing; Automatic Emotion/Depression Recognition
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Related URLs:
Depositing User: Valstar, Michel
Date Deposited: 07 Sep 2017 13:08
Last Modified: 04 May 2020 19:13
URI: https://eprints.nottingham.ac.uk/id/eprint/45489

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