Speech Emotion Recognition using State-of-Art Learning Algorithms

Abstract

© 2020, World Academy of Research in Science and Engineering. All rights reserved. Emotion is considered to be one of the significant human interaction factors. Recognizing human behavior based on emotion is often misinterpreted. However, that has not prevented the analysts from attempting to extract the information from a speech called speech recognition. In this paper, we analyzed the different algorithm’s performance in the field of speech signal classification. Considering accuracy and precision as factors, ANN showed higher results with around 80% accuracy and correctness, followed by SVM and CNN competing for each other for accuracy in between 75 and 80 percent. SVM showed close approximation between accuracy and precision, leaving random forest classifier in the last place. Our experimentation showed neural networks performed substantially in the field of speech and signal processing.