个性化
足球
情绪分析
唤醒
情感计算
考试(生物学)
价(化学)
情绪识别
多模态
计算机科学
德国的
心理学
人工智能
社会心理学
万维网
语言学
哲学
古生物学
物理
生物
法学
量子力学
政治学
作者
Shahin Amiriparian,Lukas Christ,Andreas König,Alan Cowen,Eva-Maria Meßner,Erik Cambria,Björn W. Schuller
标识
DOI:10.1145/3581783.3610943
摘要
The 4th Multimodal Sentiment Analysis Challenge (MuSe) focuses on Multimodal Prediction of Mimicked Emotions, Cross-Cultural Humour, and Personalised Recognition of Affects. The workshop takes place in conjunction with ACM Multimedia'23. We provide three datasets as part of the challenge: (i) The Hume-Vidmimic dataset which offers 30+ hours of expressive behaviour data from 557 participants. It involves mimicking and rating emotions: Approval, Disappointment, and Uncertainty. This multimodal resource is valuable for studying human emotional expressions. (ii) The 2023 edition of the Passau Spontaneous Football Coach Humor (Passau-SFCH) dataset comprises German football press conference recordings within the training set, while videos of English football press conferences are included in the unseen test set. This unique configuration offers a cross-cultural evaluation environment for humour recognition. (iii) The Ulm-Trier Social Stress Test (Ulm-TSST) dataset contains recordings of subjects under stress. It involves arousal and valence signals, with some test labels provided to aid personalisation. Based on these datasets, we formulate three multimodal affective computing challenges: (1) Mimicked Emotions Sub-Challenge (MuSe-Mimic) for categorical emotion prediction, (2) Cross-Cultural Humour Detection Sub-Challenge (MuSe-Humour) for cross-cultural humour detection, and (3) Personalisation Sub-Challenge (MuSe-Personalisation) for personalised dimensional emotion recognition. In this summary, we outline the challenge's motivation, participation guidelines, conditions, and results.
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