Login (DCU Staff Only)
Login (DCU Staff Only)

DORAS | DCU Research Repository

Explore open access research and scholarly works from DCU

Advanced Search

From Arabic user-generated content to machine translation: integrating automatic error correction

Afli, Haithem orcid logoORCID: 0000-0002-7449-4707, Aransa, Walid, Lohar, Pintu orcid logoORCID: 0000-0002-5328-1585 and Way, Andy orcid logoORCID: 0000-0001-5736-5930 (2016) From Arabic user-generated content to machine translation: integrating automatic error correction. In: 17th International Conference on Intelligent Text Processing and Computational Linguistics, 3–9 Apr 2016, Konya, Turkey.

Abstract
With the wide spread of the social media and online forums, individual users have been able to actively participate in the generation of online content in different languages and dialects. Arabic is one of the fastest growing languages used on Internet, but dialects (like Egyptian and Saudi Arabian) have a big share of the Arabic online content. There are many differences between Dialectal Arabic and Modern Standard Arabic which cause many challenges for Machine Translation of informal Arabic language. In this paper, we investigate the use of Automatic Error Correction method to improve the quality of Arabic User-Generated texts and its automatic translation. Our experiments show that the new system with automatic correction module outperforms the baseline system by nearly 22.59% of relative improvement.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Automatic Error Correction; Machine translation; pre-processing; Arabic User-Generated content
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Institutes and Centres > ADAPT
Published in: CICLING 2016: 17th International Conference on Intelligent Text Processing and Computational Linguistics, Proceedings. .
Copyright Information:© 2016
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:23234
Deposited On:02 May 2019 14:47 by Thomas Murtagh . Last Modified 05 May 2023 16:27
Documents

Full text available as:

[thumbnail of From Arabic User-Generated Content to Machine Translation.pdf]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
494kB
Downloads

Downloads

Downloads per month over past year

Archive Staff Only: edit this record