IIUM Repository

Speech emotion verification system (SEVS) based on MFCC for real time applications

Kamaruddin, Norhaslinda and Abdul Rahman, Abdul Wahab (2008) Speech emotion verification system (SEVS) based on MFCC for real time applications. In: 4th International Conference on Intelligent Environments, IE 08, 21-22 July 2008, Seattle, WA.

[img] PDF - Published Version
Restricted to Repository staff only

Download (1MB) | Request a copy

Abstract

Human recognizes speech emotions by extracting features from the speech signals received through the cochlea and later passed the information for processing. In this paper we propose the use of Mel-Frequency Cepstral Coefficient (MFCC) to extract the speech emotion information to provide both the frequency and time domain information for analysis. Since features extracted using the MFCC simulates the function of the human cochlea, neural network (NN) and fuzzy neural network algorithm namely; Multi Layer Perceptron (MLP), Adaptive Network-based Fuzzy Inference System (ANFIS) and Generic Selforganizing Fuzzy Neural Network (GenSoFNN) were used to verify the different emotions. Experimental results show potential of using these techniques to detect and distinguish three basic emotions from speech for real-time applications based on features extracted using MFCC.

Item Type: Conference or Workshop Item (Full Paper)
Additional Information: 6145/38169
Uncontrolled Keywords: Speech emotion, MFCC, MLP, ANFIS, GenSoFNN.
Subjects: T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Information and Communication Technology > Department of Computer Science
Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User: Ahmad Nazreen Mohd Shamsuri (PT)
Date Deposited: 11 Sep 2014 11:44
Last Modified: 11 Sep 2014 11:44
URI: http://irep.iium.edu.my/id/eprint/38169

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year