Automatic detection of voice disorders using self loop architecture in back propagation network
Proceedings of International Conference on Signal Processing, Communications and Networking 2008 (ICSCN2008), organised by Department of Electronics Engineering Madras Institute of Technology, Anna University in association with AU-KBC Research Centre, 4th - 6th January 2008 at Anna University, Chen...
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my.unimap-147622011-10-21T04:04:14Z Automatic detection of voice disorders using self loop architecture in back propagation network Murugesa Pandiyan, Paulraj, Prof. Madya Dr, Sazali, Yaacob, Prof. Dr. Sivanandam, S. N. Muthusamy, Hariharan, Dr. paul@unimap.edu.my Acoustic features Neural network Slope parameter Self loop scheme Proceedings of International Conference on Signal Processing, Communications and Networking 2008 (ICSCN2008), organised by Department of Electronics Engineering Madras Institute of Technology, Anna University in association with AU-KBC Research Centre, 4th - 6th January 2008 at Anna University, Chennai, Tamilnadu, India. Acoustic analysis is a non-invasive technique to detect the voice disorders and diagnose the vocal and voice disease. In the recent years, voice disease are increasing dramatically due to unhealthy social habits and voice abuse. In this paper, the detection of voice disorders based on classification of pathological voices using neural network trained by Back propagation with slope parameter improves the convergence ability of BP propagation algorithm. A simple scheme is proposed to fix the slope parameters of the bipolar sigmoidal activation function. Self loop scheme is the output of the hidden neurons feedback to itself which improved the training time and generalization of the network. The proposed algorithms provide better classification rate than conventional back propagation algorithm for the automatic detection of voices disorders. 2011-10-21T04:04:14Z 2011-10-21T04:04:14Z 2008-01-04 Article 978-1-4244-1924-1 http://hdl.handle.net/123456789/14762 en Proceedings of the International Conference on Signal Processing, Communications and Networking 2008 (ICSCN2008) Anna University |
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Acoustic features Neural network Slope parameter Self loop scheme |
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Acoustic features Neural network Slope parameter Self loop scheme Murugesa Pandiyan, Paulraj, Prof. Madya Dr, Sazali, Yaacob, Prof. Dr. Sivanandam, S. N. Muthusamy, Hariharan, Dr. Automatic detection of voice disorders using self loop architecture in back propagation network |
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Proceedings of International Conference on Signal Processing, Communications and Networking 2008 (ICSCN2008), organised by Department of Electronics Engineering Madras Institute of Technology, Anna University in association with AU-KBC Research Centre, 4th - 6th January 2008 at Anna University, Chennai, Tamilnadu, India. |
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paul@unimap.edu.my |
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paul@unimap.edu.my Murugesa Pandiyan, Paulraj, Prof. Madya Dr, Sazali, Yaacob, Prof. Dr. Sivanandam, S. N. Muthusamy, Hariharan, Dr. |
format |
Article |
author |
Murugesa Pandiyan, Paulraj, Prof. Madya Dr, Sazali, Yaacob, Prof. Dr. Sivanandam, S. N. Muthusamy, Hariharan, Dr. |
author_sort |
Murugesa Pandiyan, Paulraj, Prof. Madya Dr, |
title |
Automatic detection of voice disorders using self loop architecture in back propagation network |
title_short |
Automatic detection of voice disorders using self loop architecture in back propagation network |
title_full |
Automatic detection of voice disorders using self loop architecture in back propagation network |
title_fullStr |
Automatic detection of voice disorders using self loop architecture in back propagation network |
title_full_unstemmed |
Automatic detection of voice disorders using self loop architecture in back propagation network |
title_sort |
automatic detection of voice disorders using self loop architecture in back propagation network |
publisher |
Anna University |
publishDate |
2011 |
url |
http://dspace.unimap.edu.my/xmlui/handle/123456789/14762 |
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1643790615977132032 |