MuSe 2021 Challenge: Multimodal Emotion, Sentiment, Physiological-Emotion, and Stress Detection

Lukas Stappen, Eva Maria Meßner, Erik Cambria, Guoying Zhao, Björn W. Schuller

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

14 Zitate (Scopus)

Abstract

The 2nd Multimodal Sentiment Analysis (MuSe) 2021 Challenge-based Workshop is held in conjunction with ACM Multimedia'21. Two datasets are provided as part of the challenge. Firstly, the MuSe-CaR dataset, which focuses on user-generated, emotional vehicle reviews from YouTube, and secondly, the novel Ulm-Trier Social Stress (Ulm-TSST) dataset, which shows people in stressful circumstances. Participants are faced with four sub-challenges: predicting arousal and valence in a time- and value-continuous manner on a) MuSe-CaR (MuSe-Wilder) and b) Ulm-TSST (MuSe-Stress); c) predicting unsupervised created emotion classes on MuSe-CaR (MuSe-Sent); d) predicting a fusion of human-annotated arousal and measured galvanic skin response also as a continuous target on Ulm-TSST (MuSe-Physio). In this summary, we describe the motivation, the sub-challenges, the challenge conditions, the participation, and the most successful approaches.

OriginalspracheEnglisch
TitelMM 2021 - Proceedings of the 29th ACM International Conference on Multimedia
Herausgeber (Verlag)Association for Computing Machinery, Inc
Seiten5706-5707
Seitenumfang2
ISBN (elektronisch)9781450386517
DOIs
PublikationsstatusVeröffentlicht - 17 Okt. 2021
Extern publiziertJa
Veranstaltung29th ACM International Conference on Multimedia, MM 2021 - Virtual, Online, China
Dauer: 20 Okt. 202124 Okt. 2021

Publikationsreihe

NameMM 2021 - Proceedings of the 29th ACM International Conference on Multimedia

Konferenz

Konferenz29th ACM International Conference on Multimedia, MM 2021
Land/GebietChina
OrtVirtual, Online
Zeitraum20/10/2124/10/21

Fingerprint

Untersuchen Sie die Forschungsthemen von „MuSe 2021 Challenge: Multimodal Emotion, Sentiment, Physiological-Emotion, and Stress Detection“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren