Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/14048
Title: Feature extraction based on mel-scaled wavelet packet transform for the diagnosis of voice disorders
Authors: Murugesa Pandian, Paulraj, Prof. Madya Dr,
Sazali, Yaacob, Prof. Dr.
Muthusamy, Hariharan, Dr.
paul@unimap.edu.my
Keywords: Feature extraction
Acoustic analysis
Melscaled wavelet packet transform
Neural network
Issue Date: 25-Jun-2008
Publisher: SpringerLink
Citation: IFMBE Proceedings, vol. 21(1), 2008, pages 790-793
Series/Report no.: Proceedings of the 4th Kuala Lumpur International Conference on Biomedical Engineering 2008
Abstract: Feature extraction from the vocal signal plays very important role in the area of automatic detection of voice disorders. Many feature extraction algorithms have been developed in the last three decades based on acoustic analysis of speech signals. To provide a robust representation of speech signal in an automatic voice disorder diagnosis system, a Melscaled wavelet packet transform has been suggested. A simple neural network model is designed to test the efficacy of Melscaled wavelet packet transform based features. Experimental results show that the features derived by using Melscaled wavelet packet transform provides comparable results. The proposed features can be used as an additional acoustic indicator for the evaluation of voice disorders.
Description: Link to publisher's homepage at http://springerlink.com/
URI: http://www.springerlink.com/content/j57572n370x4x802/fulltext.pdf
http://dspace.unimap.edu.my/123456789/14048
ISBN: 978-354069138-9
ISSN: 1680-0737
Appears in Collections:Conference Papers
Sazali Yaacob, Prof. Dr.
Paulraj Murugesa Pandiyan, Assoc. Prof. Dr.
Hariharan Muthusamy, Dr.

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