Cover Image

Application of feedforward neural network for the classification of pathological voices

Organized by Universiti Teknologi MARA, 9th - 11th March 2011 at Malacca, Malaysia.

Saved in:
Bibliographic Details
Main Authors: Sazali, Yaacob, Prof. Dr., Murugesa Padiyan, Paulraj, Dr., Mohd Rizon, Mohammed Juhari, Prof. Dr., Muthusamy, Hariharan, Dr.
Other Authors: wavelet.hari@gmail.com.my
Format: Working Paper
Language:English
Published: Universiti Teknologi MARA (UiTM) 2011
Subjects:
Acoustic voice analysis
Electroglottograph (EGG)
Feature extraction
Artificial neural networks
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/14875
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.unimap-14875
record_format dspace
spelling 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)
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 voice analysis
Electroglottograph (EGG)
Feature extraction
Artificial neural networks
spellingShingle 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
description 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
_version_ 1643790647172268032
score 13.160551

Similar Items