NDLI: DWT and MFCC based human emotional speech classification using LDA

Content Provider	IEEE Xplore Digital Library
Author	Murugappan, M. Baharuddin, N.Q.I. Jerritta, S.
Copyright Year	2012
Description	Author affiliation: School of Mechatronic Engineering, University Malaysia Perlis (UniMAP), Campus Ulu Pauh, 02600, Arau, MALAYSIA (Murugappan, M.; Baharuddin, N.Q.I.; Jerritta, S.)
Abstract	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.
Starting Page	203
Ending Page	206
File Size	877831
Page Count	4
File Format	PDF
ISBN	9781457719905
e-ISBN	9781457719912
DOI	10.1109/ICoBE.2012.6179005
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-02-27
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accuracy DWT MFCC Speech recognition LDA Speech Feature extraction Wavelet analysis Emotional speech Discrete wavelet transforms Mel frequency cepstral coefficient Gender classification
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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