no code implementations • 15 Sep 2023 • Alexander Gebhard, Andreas Triantafyllopoulos, Teresa Bez, Lukas Christ, Alexander Kathan, Björn W. Schuller
Advances in passive acoustic monitoring and machine learning have led to the procurement of vast datasets for computational bioacoustic research.
no code implementations • 16 May 2023 • Niklas Mueller, Steffen Klug, Andreas Koenig, Alexander Kathan, Lukas Christ, Bjoern Schuller, Shahin Amiriparian
Integrating research on laughter, affect-as-information, and infomediaries' social evaluations of firms, we hypothesize that voiced laughter in executive communication positively affects social approval, defined as audience perceptions of affinity towards an organization.
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.
1 code implementation • 21 Dec 2022 • Lukas Christ, Shahin Amiriparian, Manuel Milling, Ilhan Aslan, Björn W. Schuller
Telling stories is an integral part of human communication which can evoke emotions and influence the affective states of the audience.
1 code implementation • 28 Sep 2022 • Lukas Christ, Shahin Amiriparian, Alexander Kathan, Niklas Müller, Andreas König, Björn W. Schuller
Our findings suggest that for the automatic analysis of humour and its sentiment, facial expressions are most promising, while humour direction can be best modelled via text-based features.
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.
no code implementations • 27 Jul 2021 • Alice Baird, Lukas Stappen, Lukas Christ, Lea Schumann, Eva-Maria Meßner, Björn W. Schuller
We utilise a Long Short-Term Memory, Recurrent Neural Network to explore the benefit of fusing these physiological signals with arousal as the target, learning from various audio, video, and textual based features.
no code implementations • 20 Apr 2021 • Shahin Amiriparian, Artem Sokolov, Ilhan Aslan, Lukas Christ, Maurice Gerczuk, Tobias Hübner, Dmitry Lamanov, Manuel Milling, Sandra Ottl, Ilya Poduremennykh, Evgeniy Shuranov, Björn W. Schuller
Text encodings from automatic speech recognition (ASR) transcripts and audio representations have shown promise in speech emotion recognition (SER) ever since.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
1 code implementation • 14 Apr 2021 • Lukas Stappen, Alice Baird, Lukas Christ, Lea Schumann, Benjamin Sertolli, Eva-Maria Messner, Erik Cambria, Guoying Zhao, Björn W. Schuller
Multimodal Sentiment Analysis (MuSe) 2021 is a challenge focusing on the tasks of sentiment and emotion, as well as physiological-emotion and emotion-based stress recognition through more comprehensively integrating the audio-visual, language, and biological signal modalities.