MuSe-Humor: Humor Detection Sub-Challenge (MuSe 2022)

Description: Predicting the presence of humor in football press conference recordings. Available modalities: audio and video, transcriptions.

Labels: windows of 2 seconds are given a binary label, indicating presence and absence of humor. 9 human annotators labelled each video.

Dataset: MuSe-Humor is based on the novel Passau-Spontaneous Football Coach Humor (Passau-SFCH) dataset. It includes press conference recordings of 10 different German Bundesliga football coaches collected in 2017. The data provided here only includes segments in which the respective coach is speaking. The training data set contains recordings of 4 coaches, development and test data each contain recordings of 3 coaches.

Change in Version 1.1: we added the manually corrected transcriptions and BERT features based on them.

General: The 3rd Multimodal Sentiment Analysis Challenge and Workshop (MuSe) 2022 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.