Supporting Undotted Arabic with Pre-trained Language Models

• URL: http://arxiv.org/abs/2111.09791v1
• Date: Thu, 18 Nov 2021 16:47:56 GMT
• Title: Supporting Undotted Arabic with Pre-trained Language Models
• Authors: Aviad Rom and Kfir Bar
• Abstract summary: We study the effect of applying pre-trained Arabic language models on "undotted" Arabic texts. We suggest several ways of supporting undotted texts with pre-trained models, without additional training, and measure their performance on two Arabic natural-language-processing tasks.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We observe a recent behaviour on social media, in which users intentionally remove consonantal dots from Arabic letters, in order to bypass content-classification algorithms. Content classification is typically done by fine-tuning pre-trained language models, which have been recently employed by many natural-language-processing applications. In this work we study the effect of applying pre-trained Arabic language models on "undotted" Arabic texts. We suggest several ways of supporting undotted texts with pre-trained models, without additional training, and measure their performance on two Arabic natural-language-processing downstream tasks. The results are encouraging; in one of the tasks our method shows nearly perfect performance.

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