Variational Autoencoders for Learning Latent Representations of Speech Emotion: A Preliminary Study
Variational Autoencoders for Learning Latent Representations of Speech Emotion: A Preliminary Study
Learning the latent representation of data in unsupervised fashion is a very interesting process that provides relevant features for enhancing the performance of a classifier.For speech emotion recognition tasks, generating effective features is crucial.Currently, handcrafted features are mostly used for speech emotion recognition, however, features learned automatically using deep learning …