A New Approach to Emotion Recognition in Conversations Based on Graph Neural Networks Research Background Emotion recognition (ER) is an important component of human-computer interaction (HCI), aiming to identify human emotional states by analyzing multimodal data such as speech, text, and video. This technology has broad application prospects in f...

Cross-Subject EEG Emotion Recognition Research Based on Multi-Scale Hyperbolic Contrastive Learning Academic Background Electroencephalography (EEG), as a physiological signal, plays an important role in the field of affective computing. Compared with traditional non-physiological cues (such as facial expressions or voice), EEG signals have higher ...

Application of Physiological Data in Human-Robot Interaction with Anthropomorphic Service Robots: Affect-HRI Dataset Background and Significance In interactions between humans and humans, as well as humans and robots, the interacting entity can influence human emotional states. Unlike humans, robots inherently cannot exhibit empathy and thus cannot...

The Gating Role of Cortical Transfer of Socially Derived Information in Emotion Recognition Background Introduction Emotion recognition and the subsequent responses are crucial for survival and maintaining social functions. However, how social information is processed to reliably recognize emotions remains unclear. In this new study, the authors re...