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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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Main Authors: Murugesa Pandiyan, Paulraj, Prof. Madya Dr,, Sazali, Yaacob, Prof. Dr., Sivanandam, S. N., Muthusamy, Hariharan, Dr.
Other Authors: paul@unimap.edu.my
Format: Article
Language:English
Published: Anna University 2011
Subjects:
Acoustic features
Neural network
Slope parameter
Self loop scheme
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/14762
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spelling 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
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 Acoustic features
Neural network
Slope parameter
Self loop scheme
spellingShingle 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
description 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.
author2 paul@unimap.edu.my
author_facet 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
_version_ 1643790615977132032
score 13.186907

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