Arabic Dialect Identification Using BERT-Based Domain Adaptation
- URL: http://arxiv.org/abs/2011.06977v1
- Date: Fri, 13 Nov 2020 15:52:51 GMT
- Title: Arabic Dialect Identification Using BERT-Based Domain Adaptation
- Authors: Ahmad Beltagy, Abdelrahman Wael, Omar ElSherief
- Abstract summary: Arabic is one of the most important and growing languages in the world.
With the rise of social media platforms such as Twitter, Arabic spoken dialects have become more in use.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Arabic is one of the most important and growing languages in the world. With
the rise of social media platforms such as Twitter, Arabic spoken dialects have
become more in use. In this paper, we describe our approach on the NADI Shared
Task 1 that requires us to build a system to differentiate between different 21
Arabic dialects, we introduce a deep learning semi-supervised fashion approach
along with pre-processing that was reported on NADI shared Task 1 Corpus. Our
system ranks 4th in NADI's shared task competition achieving a 23.09% F1 macro
average score with a simple yet efficient approach to differentiating between
21 Arabic Dialects given tweets.
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