Cross-Subject EEG Emotion Recognition Based on Temporal Asynchronous Alignment Contrastive Learning
With the advancement of science and technology, the importance of emotion research has become increasingly evident. Electroencephalography (EEG)-based emotion recognition has emerged as an active research area in recent years, owing to its objectivity and high temporal resolution. However, most existing methods focus on optimizing encoder structures to enhance feature extraction capabilities, while paying relatively little attention to similarity calculation strategies, particularly overlooking the potential temporal misalignment of responses among different subjects. To address these shortcomings, this paper draws inspiration from the late interaction mechanism of ColBERT in natural lang...
| Authors | Ying Xie, Yi Zheng, Zehui Xiao et al. |
|---|---|
| Primary category | cs.HC |
| Published | 21 May 2026 |
| Last updated at source | 21 May 2026 |
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