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Classification improvement of spoken arabic language based on radial basis function

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 9 No. 1 (2019)

DOI
10.11591/ijece.v9i1.pp402-408
ISSN
2088-8708, 2088-8708
Published
2019-02-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

The important task in the computer interaction is the languages recognition and classification. In the Arab world, there is a persistent need for the Arabic spoken language recognition To help those who have lost the upper parties in doing what they want through speech computer interaction. While, the Arabic automatic speech recognition (AASR) did not receive the desired attention from the researchers. In this paper, the Radial Basis Function(RBF) is used for the improvement of the Arabic spoken language letter. The recognition and classification process are based on three steps; these are; preprocessing, feature extraction and classification (Recognition). The Arabic Language Letters (ALL) recognition is done by using the combination between the statistical features and the Temporal Radial Basis Function for different letter situation and noisy condition. The recognition percent are from 90% - 99.375% has been gained with independent speaker, where these results are over-perform the earlier works by nearly 2.045%. The simulati.on has been made by using Matlab 2015b.

Collaboration network of the authors

7 authors · 9 co-authorship links

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  • Nahrain University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Mahmuod Hamza Al-MuifrajeAffiliation unknown1
Ghufran Mahdi HatemAffiliation unknown1
Hikmat N. AbdullahNahrain University1
Asaad Hameed SaharAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Classification improvement of spoken arabic language based on radial basis function</dc:title><dc:creator>Saeed, Thamir Rashed</dc:creator><dc:creator>Salman, Jabar</dc:creator><dc:creator>Ali, Alaa Hussein</dc:creator><dc:description>&lt;jats:p&gt;The important task in the computer interaction is the languages recognition and classification. In the Arab world, there is a persistent need for the Arabic spoken language recognition To help those who have lost the upper parties in doing what they want through speech computer interaction. While, the Arabic automatic speech recognition (AASR) did not receive the desired attention from the researchers. In this paper, the Radial Basis Function(RBF) is used for the improvement of the Arabic spoken language letter. The recognition and classification process are based on three steps; these are; preprocessing, feature extraction and classification (Recognition). The Arabic  Language Letters  (ALL) recognition is done by using the combination between the statistical features and the Temporal Radial Basis Function for different letter situation and noisy condition. The recognition percent are from 90% - 99.375% has been gained with independent speaker, where these results are over-perform the earlier works by nearly 2.045%. The simulati.on has been made by using Matlab 2015b.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2019-02-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v9i1.pp402-408</dc:identifier><dc:identifier>10.11591/ijece.v9i1.pp402-408</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 9 No 1 (2019); 402</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/11524/10616</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>