Assimilate the auditory scale with wavelet packet filters for multistyle classification of speech under stress
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Institute of Electrical and Electronics Engineers (IEEE)
2012
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| Online Access: | http://dspace.unimap.edu.my/xmlui/handle/123456789/21415 |
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my.unimap-214152013-07-23T07:49:52Z Assimilate the auditory scale with wavelet packet filters for multistyle classification of speech under stress Nurul Aida Amira, Johari Muthusamy, Hariharan, Dr. Saidatul Ardeenawatie, Awang Sazali, Yaacob, Prof. Dr. cintan.jerit@gmail.com hari@unimap.edu.my Emotional/Stressed states Wavelet packet transform Linear Discriminant Analysis Support Vector Machine Stress classification Link to publisher's homepage at http://ieeexplore.ieee.org/ Nowadays, people are having high stress level due to highworkload stress, emergency phone call and multitasking. Emotional/stress of a person affects his/her performance in daily life and speech production. The research for understanding the human emotional/stress states using speech has undergone research and development in the past two decades. This paper presents a feature extraction method based on wavelet packet decomposition for detecting the emotional or stressed states of the person. Three different wavelet packet filter bank structures are design based on Bark scale, Mel Scale and Equivalent Rectangular Bandwidth (ERB) Scale. Linear Discriminant Analysis (LDA) based classifier and Support Vector Machine (SVM) are employed as classifier to identify the emotional/stressed states of a person. In this study speech samples are taken from Speech Under Simulated and Actual Stress (SUSAS) database. Experimental result shows that the suggested method can be used to identify the stress and emotional state of a person. 2012-10-18T08:22:06Z 2012-10-18T08:22:06Z 2012-02-27 Working Paper p. 537-542 978-145771989-9 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6179076 http://hdl.handle.net/123456789/21415 en Proceedings of the International Conference on Biomedical Engineering (ICoBE 2012) Institute of Electrical and Electronics Engineers (IEEE) |
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Malaysia |
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Universiti Malaysia Perlis |
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| language |
English |
| topic |
Emotional/Stressed states Wavelet packet transform Linear Discriminant Analysis Support Vector Machine Stress classification |
| spellingShingle |
Emotional/Stressed states Wavelet packet transform Linear Discriminant Analysis Support Vector Machine Stress classification Nurul Aida Amira, Johari Muthusamy, Hariharan, Dr. Saidatul Ardeenawatie, Awang Sazali, Yaacob, Prof. Dr. Assimilate the auditory scale with wavelet packet filters for multistyle classification of speech under stress |
| description |
Link to publisher's homepage at http://ieeexplore.ieee.org/ |
| author2 |
cintan.jerit@gmail.com |
| author_facet |
cintan.jerit@gmail.com Nurul Aida Amira, Johari Muthusamy, Hariharan, Dr. Saidatul Ardeenawatie, Awang Sazali, Yaacob, Prof. Dr. |
| format |
Working Paper |
| author |
Nurul Aida Amira, Johari Muthusamy, Hariharan, Dr. Saidatul Ardeenawatie, Awang Sazali, Yaacob, Prof. Dr. |
| author_sort |
Nurul Aida Amira, Johari |
| title |
Assimilate the auditory scale with wavelet packet filters for multistyle classification of speech under stress |
| title_short |
Assimilate the auditory scale with wavelet packet filters for multistyle classification of speech under stress |
| title_full |
Assimilate the auditory scale with wavelet packet filters for multistyle classification of speech under stress |
| title_fullStr |
Assimilate the auditory scale with wavelet packet filters for multistyle classification of speech under stress |
| title_full_unstemmed |
Assimilate the auditory scale with wavelet packet filters for multistyle classification of speech under stress |
| title_sort |
assimilate the auditory scale with wavelet packet filters for multistyle classification of speech under stress |
| publisher |
Institute of Electrical and Electronics Engineers (IEEE) |
| publishDate |
2012 |
| url |
http://dspace.unimap.edu.my/xmlui/handle/123456789/21415 |
| _version_ |
1643793394340724736 |