Voice disorders identification using multilayer neural network

Joint Authors

Salhi, Lotfi
Mourad, Talbi
Sharif, Adnan

Source

The International Arab Journal of Information Technology

Issue

Vol. 7, Issue 2 (30 Apr. 2010), pp.177-185, 9 p.

Publisher

Zarqa University

Publication Date

2010-04-30

Country of Publication

Jordan

No. of Pages

9

Main Subjects

Information Technology and Computer Science

Topics

Abstract EN

In this paper we present a new method for voice disorders classification based on multilayer neural network.

The processing algorithm is based on a hybrid technique which uses the wavelets energy coefficients as input of the multilayer neural network.

The training step uses a speech database of several pathological and normal voices collected from the national hospital “Rabta-Tunis” and was conducted in a supervised mode for discrimination of normal and pathology voices and in a second step classification between neural and vocal pathologies (Parkinson, Alzheimer, laryngeal, dyslexia…).

Several simulation results will be presented in function of the disease and will be compared with the clinical diagnosis in order to have an objective evaluation of the developed tool.

American Psychological Association (APA)

Salhi, Lotfi& Mourad, Talbi& Sharif, Adnan. 2010. Voice disorders identification using multilayer neural network. The International Arab Journal of Information Technology،Vol. 7, no. 2, pp.177-185.
https://search.emarefa.net/detail/BIM-58500

Modern Language Association (MLA)

Salhi, Lotfi…[et al.]. Voice disorders identification using multilayer neural network. The International Arab Journal of Information Technology Vol. 7, no. 2 (Apr. 2010), pp.177-185.
https://search.emarefa.net/detail/BIM-58500

American Medical Association (AMA)

Salhi, Lotfi& Mourad, Talbi& Sharif, Adnan. Voice disorders identification using multilayer neural network. The International Arab Journal of Information Technology. 2010. Vol. 7, no. 2, pp.177-185.
https://search.emarefa.net/detail/BIM-58500

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical referenses : p. 184-185

Record ID

BIM-58500