Speech Emotion Recognition Framework based on User Self-referential Speech Features

This paper proposes a SER (Speech Emotion Recognition) framework using user self-referential speech features, which reflect the ROC (Rate of Change) of the corresponding feature value according to the user's emotion states. The experiments shows that using the proposed self-referential features in addition to the absolute value of speech features can improve the SER accuracy.