Dimensional Emotion Recognition from Speech Using Modulation Spectral Features and Recurrent Neural Networks

Dimensional emotion recognition (DER) from speech is used to track the dynamics of emotions for robots to naturally interact with humans. The DER system needs to obtain frame-level feature sequences by selecting the appropriate acoustic features and duration. Moreover, these sequences should reflect the dynamic characteristics of the utterance. Temporal modulation cues are good at capturing the dynamic characteristics for speech perception and...