A Review on Automatic Speech Emotion Recognition with an Experiment Using Multilayer Perceptron Classifier

dc.contributor.author	Sardar, Abdullah Al Mamun
dc.contributor.author	Islam, Md. Sanzidul
dc.contributor.author	Bhuiyan, Touhid
dc.date.accessioned	2021-05-19T04:22:53Z
dc.date.available	2021-05-19T04:22:53Z
dc.date.issued	2020-11-28
dc.identifier.uri	http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/5743
dc.description.abstract	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.	en_US
dc.language.iso	en_US	en_US
dc.publisher	Springer	en_US
dc.subject	Emotion recognition	en_US
dc.subject	Chroma	en_US
dc.subject	Mel-spectrogram frequency	en_US
dc.title	A Review on Automatic Speech Emotion Recognition with an Experiment Using Multilayer Perceptron Classifier	en_US
dc.type	Article	en_US