An autoencoder-based feature level fusion for speech emotion recognition
Although speech emotion recognition is challenging, it has broad application prospects in human-computer interaction.Building a system that can accurately and stably recognize emotions from human languages can provide a better user experience.However, the current unimodal pycom expansion board 2.0 emotion feature representations are not distinctive