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164895

A Neural Network Based Arabic Speech Filing System.

Article

Last updated: 22 Jan 2023

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Subjects

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Tags

Electrical Engineering

Abstract

A natural man - machine communication with word processors requires the integration of speech recognition techniques. Speech recognition task is a difficult problem because of its temporal nature and the possibility of the presence of noise. Therefore, it is difficult to extract significant features by using the traditional techniques. Artificial neural networks introduce simple and fast learning techniques for this problem. This paper introduces the application of a three layer neural network for converting spoken Arabic words into Arabic text. We describe a supervised learning method which is based on the well known back propagation technique. The designed network proves itself to be speaker independent and noise immune word spotting guarantees invariance under translation in time.
  A user friendly word processor  should nave intelligent interfaces such as the speaker interface and the hand writing interface. In this work we introduce the first interface. It is expected that neural network based speech-to-text transcription systems should have a significant effect on office

DOI

10.21608/bfemu.2021.164895

Authors

First Name

Ahmed

Last Name

Tolba

MiddleName

El-Saeed

Affiliation

Assistant Professor., Electrical Engineering Department ., University of Suez-Canal., Port-Said., Egypt.

Email

ah_shohdy@mans.edu.eg

City

Port-Said

Orcid

-

First Name

Ibrahim

Last Name

Ismail

MiddleName

Ibrahim

Affiliation

Electronics and Communications Department., University of Helwan., Cairo., Egypt.

Email

-

City

Cairo

Orcid

-

Volume

18

Article Issue

1

Related Issue

24033

Issue Date

1993-03-01

Receive Date

1993-01-11

Publish Date

2021-03-01

Page Start

72

Page End

80

Print ISSN

1110-0923

Online ISSN

2735-4202

Article File

BFEMU_Volume 18_Issue 1_Pages 72-80.pdf

PDF . 357.4kB

Link

https://bfemu.journals.ekb.eg/article_164895.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=164895

Order

3

Type

Research Studies

Type Code

1,205

Publication Type

Journal

Publication Title

MEJ. Mansoura Engineering Journal

Publication Link

https://bfemu.journals.ekb.eg/

MainTitle

-

Details

Type

Article

Created At

22 Jan 2023