MuSe '24: The 5th Multimodal Sentiment Analysis Challenge and Workshop: Social Perception & Humor

The 5th Multimodal Sentiment Analysis Challenge (MuSe), a workshop in conjunction with ACM Multimedia '24, is focused on Multimodal Machine Learning in the domain of Affective Computing. Two different sub-challenges are proposed: Social Perception Sub-Challenge(MuSe-Perception) is a regression task on 16 different perceived characteristics including arrogance, sincerity and likability. For this, the novel LMU-ELP dataset is introduced, consisting of short audiovisual recordings of 177 subjects annotated by MTurk workers. Cross-Cultural Humour Detection Sub-Challenge(MuSe-Humor) poses the problem of cross-cultural humor recognition. An extension of the Passau Spontaneous Football Coach Humour (Passau-SFCH) dataset featuring football coach press conference recordings is utilized in this task. The training set consists of German data, while the test data comprises English recordings only. In both sub-challenges, audiovisual recordings, transcripts, pre-computed features, and baseline models are made available. In this summary, we detail the challenge's motives, organization, participation statistics, and results.

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Published
2024-10-23
DOI
https://doi.org/10.1145/3689062.3695939
Primary Topic
Humor Studies and Applications
Type
article
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article

MuSe '24: The 5th Multimodal Sentiment Analysis Challenge and Workshop: Social Perception & Humor

Shahin Amiriparian, Björn W. Schuller, Simone Maria Eulitz, Andreas König et al.
Humor Studies and Applications
article

MuSe '24: The 5th Multimodal Sentiment Analysis Challenge and Workshop: Social Perception & Humor

Shahin Amiriparian, Björn W. Schuller, Simone Maria Eulitz, Andreas König, Lukas Christ, Erik Cambria
article en

Abstract

The 5th Multimodal Sentiment Analysis Challenge (MuSe), a workshop in conjunction with ACM Multimedia '24, is focused on Multimodal Machine Learning in the domain of Affective Computing. Two different sub-challenges are proposed: Social Perception Sub-Challenge(MuSe-Perception) is a regression task on 16 different perceived characteristics including arrogance, sincerity and likability. For this, the novel LMU-ELP dataset is introduced, consisting of short audiovisual recordings of 177 subjects annotated by MTurk workers. Cross-Cultural Humour Detection Sub-Challenge(MuSe-Humor) poses the problem of cross-cultural humor recognition. An extension of the Passau Spontaneous Football Coach Humour (Passau-SFCH) dataset featuring football coach press conference recordings is utilized in this task. The training set consists of German data, while the test data comprises English recordings only. In both sub-challenges, audiovisual recordings, transcripts, pre-computed features, and baseline models are made available. In this summary, we detail the challenge's motives, organization, participation statistics, and results.

Nanyang Technological University (SG), University of Augsburg (DE), University of Passau (DE), LMU Klinikum (DE), Imperial College London (GB), Technical University of Munich (DE), Ludwig-Maximilians-Universität München (DE)
Reduced inequalities
Openalex Percentile: Top 76%
Humor Studies and Applications
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MuSe '24: The 5th Multimodal Sentiment Analysis Challenge and Workshop: Social Perception & Humor — Shahin Amiriparian, Björn W. Schuller, et al. · (2024) | TGRS Research Map | TGRS