MuSe 2022 Challenge: Multimodal Humour, Emotional Reactions, and Stress

Shahin Amiriparian, Lukas Christ, Andreas König, Eva-Maria Meßner, Alan Cowen, Erik Cambria, Björn W. Schuller

Abstract: The 3rd Multimodal Sentiment Analysis Challenge (MuSe) focuses on multimodal affective computing. The workshop is held in conjunction with ACM Multimedia'22. Three datasets are provided as part of the challenge: (i) the Passau Spontaneous Football Coach Humor (Passau-SFCH) dataset which contains humour-tagged audio-visual data of German football coaches, (ii) the Hume-Reaction dataset, which contains annotations on how people respond to emotional stimuli in terms of seven different emotional expression intensities, and (iii) the Ulm-Trier Social Stress Test (Ulm-TSST) dataset, which consists of audio-visual recordings labelled with continuous emotion values of individuals in stressful circumstances. Based on these datasets three affective computing challenges are defined: 1) Humor Detection Sub-Challenge (MuSe-Humor), for spontaneous humour recognition, 2) Emotional Reactions Sub-Challenge (MuSe-Reaction), for prediction of seven fine-grained in-the-wild' emotions, and 3) Emotional Stress Sub-Challenge (MuSe-Stress), for continuous prediction of stressed emotion values. In this summary, we describe the motivation behind the challenge, participation and its conditions, as well as the outcomes. The complete MuSe'22 workshop proceedings are available at: https://dl.acm.org/doi/proceedings/10.1145/3551876