Development of Techniques for Speech Emotion Recognition (SER) In the Context of Deep Learning

Understanding emotions from voice signals is a crucial yet difficult aspect of human-computer interaction (HCI). Many methods, including many well-known speech analysis and classification methods, have been used to extract emotions from signals in the literature on speech emotion recognition (SER). Deep learning methodologies have recently been presented as a replacement to traditional SER procedures. This paper presents an overview of deep learning algorithms for speech-based emotion recognition and evaluates some recent work that makes use of these methods. The review discusses the databases used, the emotions retrieved, the advancements made in voice emotion recognition, and its limits.