Name
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. (C) 2020 Elsevier Inc. All rights reserved. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.cosrev.2020.100305 | COMPUTER SCIENCE REVIEW |
Keywords | DocType | Volume |
Natural language processing, Machine Translation, Arabic Machine Translation, Arabic language, Deep learning | Journal | 38 |
ISSN | Citations | PageRank |
1574-0137 | 1 | 0.43 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohamed Seghir Hadj Ameur | 1 | 1 | 0.43 |
| Farid Meziane | 2 | 308 | 37.98 |
| Ahmed Guessoum | 3 | 7 | 2.74 |