Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6902057 | Procedia Computer Science | 2017 | 8 Pages |
Abstract
This paper shows that, by detecting more linguistic patterns and integrating them into En-Ar SMT system, translation quality could be improved with other integration methods. Yet, the results show which path is worth to follow and clarifies the perspective that linguistic features are not handled properly in the statistically learned models.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Sara Ebrahim, Doaa Hegazy, Mostafa Gadal-Haqq M. Mostafa, Samhaa R. El-Beltagy,