1 code implementation • 5 May 2023 • Lukas Christ, Shahin Amiriparian, Alice Baird, Alexander Kathan, Niklas Müller, Steffen Klug, Chris Gagne, Panagiotis Tzirakis, Eva-Maria Meßner, Andreas König, Alan Cowen, Erik Cambria, Björn W. Schuller
Participants predict the presence of spontaneous humour in a cross-cultural setting.
The fifth Affective Behavior Analysis in-the-wild (ABAW) Competition is part of the respective ABAW Workshop which will be held in conjunction with IEEE Computer Vision and Pattern Recognition Conference (CVPR), 2023.
This is the Proceedings of the ACII Affective Vocal Bursts Workshop and Competition (A-VB).
The first, ExVo-MultiTask, requires participants to train a multi-task model to recognize expressed emotions and demographic traits from vocal bursts.
The ACII Affective Vocal Bursts Workshop & Competition is focused on understanding multiple affective dimensions of vocal bursts: laughs, gasps, cries, screams, and many other non-linguistic vocalizations central to the expression of emotion and to human communication more generally.
1 code implementation • 23 Jun 2022 • Lukas Christ, Shahin Amiriparian, Alice Baird, Panagiotis Tzirakis, Alexander Kathan, Niklas Müller, Lukas Stappen, Eva-Maria Meßner, Andreas König, Alan Cowen, Erik Cambria, Björn W. Schuller
For this year's challenge, we feature three datasets: (i) the Passau Spontaneous Football Coach Humor (Passau-SFCH) dataset that contains audio-visual recordings of German football coaches, labelled for the presence of humour; (ii) the Hume-Reaction dataset in which reactions of individuals to emotional stimuli have been annotated with respect to seven emotional expression intensities, and (iii) the Ulm-Trier Social Stress Test (Ulm-TSST) dataset comprising of audio-visual data labelled with continuous emotion values (arousal and valence) of people in stressful dispositions.
ExVo 2022, includes three competition tracks using a large-scale dataset of 59, 201 vocalizations from 1, 702 speakers.
Understanding emotion expressed in language has a wide range of applications, from building empathetic chatbots to detecting harmful online behavior.
Ranked #1 on Emotion Classification on GoEmotions