Speech Emotion Recognition Using Deep Learning

Abstract

Abstract: Due to different technical developments, speech signals have evolved into a kind of human-machine communication in the digital age. Recognizing the emotions of the person behind his or her speech is a crucial part of Human-Computer Interaction (HCI). Many methods, including numerous well-known speech analysis and classification algorithms, have been employed to extract emotions from signals in the literature on voice emotion recognition (SER). Speech Emotion Recognition (SER) approaches have become obsolete as the Deep Learning concept has come into play. In this paper, the algorithm for identifying speech-based emotions is implemented using deep learning. It also provides an overview of deep learning methodologies and examines some recent research that makes use of these methods. It makes use of a dataset of various emotional voices and then aids in the identification of that emotion. It will be beneficial for the computers or robots to understand humans more clearly and function in accordance with it.