Creating Resources for Dialectal Arabic from a Single Annotation: A Case Study on Egyptian and Levantine

Ramy Eskander, Nizar Habash, Owen Rambow, Arfath Pasha


Abstract
Arabic dialects present a special problem for natural language processing because there are few resources, they have no standard orthography, and have not been studied much. However, as more and more written dialectal Arabic is found in social media, NLP for Arabic dialects becomes an important goal. We present a methodology for creating a morphological analyzer and a morphological tagger for dialectal Arabic, and we illustrate it on Egyptian and Levantine Arabic. To our knowledge, these are the first analyzer and tagger for Levantine.
Anthology ID:
C16-1326
Volume:
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
Month:
December
Year:
2016
Address:
Osaka, Japan
Venue:
COLING
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
3455–3465
URL:
https://www.aclweb.org/anthology/C16-1326
DOI:
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PDF:
https://www.aclweb.org/anthology/C16-1326.pdf