A case study of improving English-Arabic translation using the transformer model
Joint Authors
Alfonse, Marco
Jamal, Dunya
Jimenez-Zafra, Salud Maria
Arif, Mustafa M.
Source
International Journal of Intelligent Computing and Information Sciences
Issue
Vol. 23, Issue 2 (30 Jun. 2023), pp.105-115, 11 p.
Publisher
Ain Shams University Faculty of Computer and Information Sciences
Publication Date
2023-06-30
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
Arabic is a language with rich morphology and few resources.
Arabic is therefore recognized as one of the most challenging languages for machine translation.
the study of translation into Arabic has received significantly less attention than that of European languages.
consequently, further research into Arabic machine translation quality needs more investigation.
this paper proposes a translation model between Arabic and English based on neural machine translation (NMT).
the proposed model employs a transformer with multi-head attention.
it combines a feed-forward network with a multi-head attention mechanism.
the NMT proposed model has demonstrated its effectiveness in improving translation by achieving an impressive accuracy of 97.68%, a loss of 0.0778, and a near-perfect bilingual evaluation understudy (BLEU) score of 99.95.
future work will focus on exploring more effective ways of addressing the evaluation and quality estimation of NMT for low-data resource languages, which are often challenging as a result of the scarcity of reference translations and human annotators.
American Psychological Association (APA)
Jamal, Dunya& Alfonse, Marco& Jimenez-Zafra, Salud Maria& Arif, Mustafa M.. 2023. A case study of improving English-Arabic translation using the transformer model. International Journal of Intelligent Computing and Information Sciences،Vol. 23, no. 2, pp.105-115.
https://search.emarefa.net/detail/BIM-1486288
Modern Language Association (MLA)
Jamal, Dunya…[et al.]. A case study of improving English-Arabic translation using the transformer model. International Journal of Intelligent Computing and Information Sciences Vol. 23, no. 2 (Jun. 2023), pp.105-115.
https://search.emarefa.net/detail/BIM-1486288
American Medical Association (AMA)
Jamal, Dunya& Alfonse, Marco& Jimenez-Zafra, Salud Maria& Arif, Mustafa M.. A case study of improving English-Arabic translation using the transformer model. International Journal of Intelligent Computing and Information Sciences. 2023. Vol. 23, no. 2, pp.105-115.
https://search.emarefa.net/detail/BIM-1486288
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 114-115
Record ID
BIM-1486288