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DWT and MFCC based human emotional speech classification using LDA

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Main Authors: Murugappan, Muthusamy, Dr., Nurul Qasturi Idayu, Baharuddin, Jeritta, S
Other Authors: murugappan@unimap.edu.my
Format: Working Paper
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2012
Subjects:
Gender classification
Emotional speech
Discrete Wavelet Transform (DWT)
Mel Frequency Cepstrum Coefficients (MFCC)
Linear Discriminant Analysis (LDA)
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/21295
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spelling my.unimap-212952014-09-02T06:37:37Z DWT and MFCC based human emotional speech classification using LDA Murugappan, Muthusamy, Dr. Nurul Qasturi Idayu, Baharuddin Jeritta, S murugappan@unimap.edu.my Gender classification Emotional speech Discrete Wavelet Transform (DWT) Mel Frequency Cepstrum Coefficients (MFCC) Linear Discriminant Analysis (LDA) Link to publisher's homepage at http://ieeexplore.ieee.org/ Recent years, identification of gender based on emotional speech is one of the active research areas in developing intelligent human machine interactive (HMI) systems and biometric system. This work aims to identify the gender of the speaker through emotional speech. Two different features extraction methods such as Discrete Wavelet Transform (DWT) and Mel Frequency Cepstrum Coefficients (MFCC) are used for extracting the statistical features from the emotional speech signals. Three different value of MFCC coefficients (13, 15, and 20) and Daubechies wavelet function with three different orders (dB4, dB6 and dB8) in Discrete Wavelet Transform (DWT) were studied and compared to analyze their effect on emotional speech classification. Gender classification was done using Linear Discriminant Analysis (LDA) classifier. As a result of this study, 20 MFCC coefficient gives the highest classification accuracy (angry: 99.54 %; happy: 99.76 %; sad: 99.91 %) on classifying three emotions compared to DWT. Complete comparison of two different feature extraction methods on classifying three emotional speech using LDA is given for justifying our system performance. 2012-10-10T09:14:31Z 2012-10-10T09:14:31Z 2012-02-27 Working Paper p. 203-206 978-145771989-9 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6179005 http://hdl.handle.net/123456789/21295 en Proceedings of the International Conference on Biomedical Engineering (ICoBE 2012) Institute of Electrical and Electronics Engineers (IEEE)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Gender classification
Emotional speech
Discrete Wavelet Transform (DWT)
Mel Frequency Cepstrum Coefficients (MFCC)
Linear Discriminant Analysis (LDA)
spellingShingle Gender classification
Emotional speech
Discrete Wavelet Transform (DWT)
Mel Frequency Cepstrum Coefficients (MFCC)
Linear Discriminant Analysis (LDA)
Murugappan, Muthusamy, Dr.
Nurul Qasturi Idayu, Baharuddin
Jeritta, S
DWT and MFCC based human emotional speech classification using LDA
description Link to publisher's homepage at http://ieeexplore.ieee.org/
author2 murugappan@unimap.edu.my
author_facet murugappan@unimap.edu.my
Murugappan, Muthusamy, Dr.
Nurul Qasturi Idayu, Baharuddin
Jeritta, S
format Working Paper
author Murugappan, Muthusamy, Dr.
Nurul Qasturi Idayu, Baharuddin
Jeritta, S
author_sort Murugappan, Muthusamy, Dr.
title DWT and MFCC based human emotional speech classification using LDA
title_short DWT and MFCC based human emotional speech classification using LDA
title_full DWT and MFCC based human emotional speech classification using LDA
title_fullStr DWT and MFCC based human emotional speech classification using LDA
title_full_unstemmed DWT and MFCC based human emotional speech classification using LDA
title_sort dwt and mfcc based human emotional speech classification using lda
publisher Institute of Electrical and Electronics Engineers (IEEE)
publishDate 2012
url http://dspace.unimap.edu.my/xmlui/handle/123456789/21295
_version_ 1643793338219888640
score 13.160551

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