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.
1 code implementation • 30 Apr 2020 • Lukas Stappen, Alice Baird, Georgios Rizos, Panagiotis Tzirakis, Xinchen Du, Felix Hafner, Lea Schumann, Adria Mallol-Ragolta, Björn W. Schuller, Iulia Lefter, Erik Cambria, Ioannis Kompatsiaris
Multimodal Sentiment Analysis in Real-life Media (MuSe) 2020 is a Challenge-based Workshop focusing on the tasks of sentiment recognition, as well as emotion-target engagement and trustworthiness detection by means of more comprehensively integrating the audio-visual and language modalities.
1 code implementation • 25 Jul 2021 • Lukas Stappen, Lea Schumann, Benjamin Sertolli, Alice Baird, Benjamin Weigel, Erik Cambria, Björn W. Schuller
With this in mind, the MuSe-Toolbox provides the functionality to run exhaustive searches for meaningful class clusters in the continuous gold standards.
no code implementations • 15 Jan 2021 • Lukas Stappen, Alice Baird, Lea Schumann, Björn Schuller
Truly real-life data presents a strong, but exciting challenge for sentiment and emotion research.
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.