Human–machine interaction is becoming popular day by day; to interact with machine, speech emotion recognition is as important as human to human interaction. In this research, we demonstrate a speech emotion recognition system which takes speech as input and classify emotions that the speech contains. We choose multilayer perceptron (MLP) classifier to do this task. Features that we have extracted from speech are mel-frequency cepstral coefficients (MFCC), chroma and mel-spectrogram frequency. RADVES dataset has been used and we have got 73% accuracy.
Sardar, A. A. M., Sanzidul Islam, M., & Bhuiyan, T. (2021). A Review on Automatic Speech Emotion Recognition with an Experiment Using Multilayer Perceptron Classifier. In Advances in Intelligent Systems and Computing (Vol. 1248, pp. 381–388). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-15-7394-1_36