Arabic machine translation: A survey of the latest trends and challenges

Journal article

Ameur, M.S.H., Meziane, Farid and Guessoum, Ahmed 2020. Arabic machine translation: A survey of the latest trends and challenges. Computer Science Review. 38, p. 100305. https://doi.org/10.1016/j.cosrev.2020.100305
AuthorsAmeur, M.S.H., Meziane, Farid and Guessoum, Ahmed
Abstract

Given that Arabic is one of the most widely used languages in the world, the task of Arabic Machine Translation (MT) has recently received a great deal of attention from the research community. Indeed, the amount of research that has been devoted to this task has led to some important achievements and improvements. However, the current state of Arabic MT systems has not reached the quality achieved for some other languages. Thus, much research work is still needed to improve it. This survey paper introduces the Arabic language, its characteristics, and the challenges involved in its translation. It provides the reader with a full summary of the important research studies that have been accomplished with regard to Arabic MT along with the most important tools and resources that are available for building and testing new Arabic MT systems. Furthermore, the survey paper discusses the current state of Arabic MT and provides some insights into possible future research directions.

KeywordsNatural language processing; Machine Translation; Arabic Machine Translation; Arabic language; Deep learning
Year2020
JournalComputer Science Review
Journal citation38, p. 100305
PublisherElsevier
ISSN15740137
Digital Object Identifier (DOI)https://doi.org/10.1016/j.cosrev.2020.100305
Web address (URL)http://hdl.handle.net/10545/625192
hdl:10545/625192
Publication dates15 Sep 2020
Publication process dates
Deposited23 Sep 2020, 08:14
Accepted04 Sep 2020
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© 2020 Elsevier Inc. All rights reserved.

ContributorsUniversity of Science and Technology Houari Boumediene (USTHB), Algeria and University of Derby
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