Alghifari, Muhammad Fahreza and Gunawan, Teddy Surya and Kartiwi, Mira (2018) Speech emotion recognition using deep feedforward neural network. Indonesian Journal of Electrical Engineering and Computer Science, 10 (2). pp. 554-561. ISSN 2502-4752
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Abstract
Speech emotion recognition (SER) is currently a research hotspot due to its challenging nature but bountiful future prospects. The objective of this research is to utilize Deep Neural Networks (DNNs) to recognize human speech emotion. First, the chosen speech feature Mel-frequency cepstral coefficient (MFCC) were extracted from raw audio data. Second, the speech features extracted were fed into the DNN to train the network. The trained network was then tested onto a set of labelled emotion speech audio and the recognition rate was evaluated. Based on the accuracy rate the MFCC, number of neurons and layers are adjusted for optimization. Moreover, a custom-made database is introduced and validated using the network optimized. The optimum configuration for SER is 13 MFCC, 12 neurons and 2 layers for 3 emotions and 25 MFCC, 21 neurons and 4 layers for 4 emotions, achieving a total recognition rate of 96.3% for 3 emotions and 97.1% for 4 emotions.
Item Type: | Article (Journal) |
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Additional Information: | 5588/62495 |
Uncontrolled Keywords: | Deep neural network, Mel-frequency cepstral coefficients (MFCC), Speech emotion recognition (SER) |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering |
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Engineering > Department of Electrical and Computer Engineering Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System |
Depositing User: | Prof. Dr. Teddy Surya Gunawan |
Date Deposited: | 27 Mar 2018 16:11 |
Last Modified: | 09 Aug 2018 15:46 |
URI: | http://irep.iium.edu.my/id/eprint/62495 |
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