SCHuBERT: A Real-Time End-to-End Model for Piano Music Emotion Recognition.

In this study, we present SCHuBERT, a real-time end-to-end Piano Music Emotion Recognition (PMER) system that operates directly on raw audio and fine-tunes DistilHuBERT for short-window classification on the Valence–Arousal plane. Designed for low latency and high responsiveness, the system is particularly well suited for immersive applications such as virtual and augmented reality. Compared with both audio- and symbolic-domain baselines, SCHuBERT achieves strong accuracy in four-quadrant classification as well as in binary arousal and valence tasks, while maintaining low computational overhead for real-time operation.