Augmenting Generative Adversarial Networks for Speech Emotion Recognition
Augmenting Generative Adversarial Networks for Speech Emotion Recognition
Generative adversarial networks (GANs) have shown potential in learning emotional attributes and generating new data samples.However, their performance is usually hindered by the unavailability of larger speech emotion recognition (SER) data.In this work, we propose a framework that utilises the mixup data augmentation scheme to augment the GAN in feature …