MuSe-Personalisation: Personalisation Sub-Challenge (MuSe 2023)

Description: Predicting valence and arousal of individuals in a stressed disposition, as induced by the Trier Social Stress Test (TSST) protocol. Available modalities: audio, video, text and physiological signals (respiratory rate, ECG, BPM).

Labels: The valence labels are obtained by fusing the ratings of three human annotators. For arousal, in contrast, two human annotations have been fused with the TSST subject's electrodermal activity (EDA) signal in order to obtain a more objective arousal gold standard. Hence, this sub-challenge is not identical to the 2021 MuSe-Stress sub-challenge.

Dataset: MuSe-Stress is based on the Ulm-TSST data set as introduced in the MuSe 2021 challenge. It contains 69 recordings of individuals during a Trier Social Stress Test (TSST). In order to facilitate personalisation, parts of the test data labels are provided. Overall, about 6 hours of recordings are provided. The data is split in a speaker-independent manner with the training data set comprising 41 individuals, development and test each comprising 14 individuals. This split is identical to the split used in the MuSe 2022 challenge.

General: The 4th Multimodal Sentiment Analysis Challenge and Workshop (MuSe) 2023 adresses research questions that are of interest to affective computing, machine learning and multimodal signal processing communities and encourages a fusion of their disciplines. The goal of the MuSe workshop and challenge is to gain new insights into the merits of each of the core modalities and to serve as a stimulating environment for the development and evaluation of multimodal affect recognition approaches.