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Speech emotion recognition using deep neural networks: matlab implementation

Ahmad Qadri, Syed Asif and Gunawan, Teddy Surya and Kartiwi, Mira (2021) Speech emotion recognition using deep neural networks: matlab implementation. LAP LAMBERT Academic Publishing. ISBN 978-620-3-46534-1

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Abstract

The key issues pivotal for successful Speech Emotion Recognition (SER) system are driven by a selection of proper emotional feature extraction techniques. In this book, Mel-frequency Cepstral Coefficient (MFCC) and Teager Energy Operator (TEO) along with a fusion of MFCC and TEO is examined over multilingual databases consisting of English, German and Hindi languages. Deep Neural Networks (DNN) has been used for the classification of the different emotions considered, including happy, sad, angry, and neutral. A sample of Matlab code implementation is provided in this book. The proposed system could be implemented especially in the customer service application, in which TEO-based features and DNN could be used to better handle customers during a conversation.

Item Type: Book
Additional Information: 5588/88786
Uncontrolled Keywords: Speech emotion recognition MFCC TEO Fusion Deep neural networks Matlab
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: Dr Teddy Surya Gunawan
Date Deposited: 12 Mar 2021 11:56
Last Modified: 12 Mar 2021 11:56
URI: http://irep.iium.edu.my/id/eprint/88786

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