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cs.CV2024
Textualized and Feature-based Models for Compound Multimodal Emotion Recognition in the Wild
Nicolas Richet, Soufiane Belharbi, Haseeb Aslam +8
Systems for multimodal emotion recognition (ER) are commonly trained to extract features from different modalities (e.g., visual, audio, and textual) that are combined to predict i…
cs.CL2024
Improving Language Models for Emotion Analysis: Insights from Cognitive Science
Constant Bonard, Gustave Cortal
We propose leveraging cognitive science research on emotions and communication to improve language models for emotion analysis. First, we present the main emotion theories in psych…
cs.CL2024
Sequence-to-Sequence Language Models for Character and Emotion Detection in Dream Narratives
Gustave Cortal
The study of dreams has been central to understanding human (un)consciousness, cognition, and culture for centuries. Analyzing dreams quantitatively depends on labor-intensive, man…