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Real-Time Arabic Speech Recognition

by Zaid Y. Mohammed, Abdul Sattar M. Khidhir
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 81 - Number 4
Year of Publication: 2013
Authors: Zaid Y. Mohammed, Abdul Sattar M. Khidhir
10.5120/14003-2048

Zaid Y. Mohammed, Abdul Sattar M. Khidhir . Real-Time Arabic Speech Recognition. International Journal of Computer Applications. 81, 4 ( November 2013), 43-45. DOI=10.5120/14003-2048

@article{ 10.5120/14003-2048,
author = { Zaid Y. Mohammed, Abdul Sattar M. Khidhir },
title = { Real-Time Arabic Speech Recognition },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 81 },
number = { 4 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 43-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume81/number4/14003-2048/ },
doi = { 10.5120/14003-2048 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:55:13.411399+05:30
%A Zaid Y. Mohammed
%A Abdul Sattar M. Khidhir
%T Real-Time Arabic Speech Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 81
%N 4
%P 43-45
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Speech recognition system needs to perform a high complex calculation and short time to complete it. This is a big challenge for the real-time systems. However, using a simple and fast algorithm may do this task for the slow systems. Thus, the main objective of this paper is to design and implement a Real-Time Arabic Speech Recognition system using MATLAB environment. It is capable of accurately identifying some letters while remaining simple and fast. It uses the Mel-Frequency Cepstral Coefficients (MFCCs) as a feature extraction and Euclidean distance to compare the test sound and the database. A recognition rate of 89. 6% has been reached.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Feature extraction Mel-Frequency Cepstral Coefficients (MFCCs) Feature match.

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