Application of feedforward neural network for the classification of pathological voices
Organized by Universiti Teknologi MARA, 9th - 11th March 2011 at Malacca, Malaysia.
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Universiti Teknologi MARA (UiTM)
2011
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my.unimap-148752011-10-24T03:53:00Z Application of feedforward neural network for the classification of pathological voices Sazali, Yaacob, Prof. Dr. Murugesa Padiyan, Paulraj, Dr. Mohd Rizon, Mohammed Juhari, Prof. Dr. Muthusamy, Hariharan, Dr. wavelet.hari@gmail.com.my paul@kukum.edu.my Acoustic voice analysis Electroglottograph (EGG) Feature extraction Artificial neural networks Organized by Universiti Teknologi MARA, 9th - 11th March 2011 at Malacca, Malaysia. This paper present the application of feed forward neural network for the classification of pathological voices based on the on the acoustic analysis and EGG features. Acoustic analysis is a non-invasive technique based on digital processing of the speech signal. Electroglottography is a method of obtaining vibration signal related to the laryngeal phonatory function. The Electroglottograph (EGG) is an instrument that register the contact between the vocal folds as a time-varying signal. The time domain voice parameters are computed from the extracted pitch data. In this paper, a Feedback Neural Network is employed for the classification of pathological voices. The Acoustic parameters extracted from the speech signal and the features from the Electroglottography from the input to the neural network distinguish the voice as pathological or a non-pathological voice. 2011-10-24T03:53:00Z 2011-10-24T03:53:00Z 2007-03-09 Working Paper p. 84-86 978-983-42747-7-7 http://hdl.handle.net/123456789/14875 en Proceedings of the 3rd International Colloquium on Signal Processing and its Application (CSPA 2007) Universiti Teknologi MARA (UiTM) |
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Acoustic voice analysis Electroglottograph (EGG) Feature extraction Artificial neural networks |
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Acoustic voice analysis Electroglottograph (EGG) Feature extraction Artificial neural networks Sazali, Yaacob, Prof. Dr. Murugesa Padiyan, Paulraj, Dr. Mohd Rizon, Mohammed Juhari, Prof. Dr. Muthusamy, Hariharan, Dr. Application of feedforward neural network for the classification of pathological voices |
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Organized by Universiti Teknologi MARA, 9th - 11th March 2011 at Malacca, Malaysia. |
author2 |
wavelet.hari@gmail.com.my |
author_facet |
wavelet.hari@gmail.com.my Sazali, Yaacob, Prof. Dr. Murugesa Padiyan, Paulraj, Dr. Mohd Rizon, Mohammed Juhari, Prof. Dr. Muthusamy, Hariharan, Dr. |
format |
Working Paper |
author |
Sazali, Yaacob, Prof. Dr. Murugesa Padiyan, Paulraj, Dr. Mohd Rizon, Mohammed Juhari, Prof. Dr. Muthusamy, Hariharan, Dr. |
author_sort |
Sazali, Yaacob, Prof. Dr. |
title |
Application of feedforward neural network for the classification of pathological voices |
title_short |
Application of feedforward neural network for the classification of pathological voices |
title_full |
Application of feedforward neural network for the classification of pathological voices |
title_fullStr |
Application of feedforward neural network for the classification of pathological voices |
title_full_unstemmed |
Application of feedforward neural network for the classification of pathological voices |
title_sort |
application of feedforward neural network for the classification of pathological voices |
publisher |
Universiti Teknologi MARA (UiTM) |
publishDate |
2011 |
url |
http://dspace.unimap.edu.my/xmlui/handle/123456789/14875 |
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1643790647172268032 |
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13.214268 |