Emotion Model

Emotion modeling in artificial intelligence focuses on developing computational representations of human emotions to enable more natural and empathetic human-computer interaction. Current research emphasizes creating unified models that integrate various emotion representations (e.g., canonical, compound, arousal-valence) and leverage techniques like attention mechanisms, contrastive learning, and ensemble methods to improve accuracy and interpretability. These advancements are crucial for enhancing applications such as chatbots, speech synthesis, and visual art comprehension, ultimately leading to more sophisticated and emotionally intelligent AI systems.