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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 7 of 7 1 Pre-Training BERT on Arabic Tweets: Practical Considerations ... Abdelali, Ahmed; Hassan, Sabit; Mubarak, Hamdy. - : arXiv, 2021 BASE Show details 2 Arabic Offensive Language on Twitter: Analysis and Experiments ... Mubarak, Hamdy; Rashed, Ammar; Darwish, Kareem. - : arXiv, 2020 BASE Show details 3 Arabic Dialect Identification in the Wild ... Abdelali, Ahmed; Mubarak, Hamdy; Samih, Younes. - : arXiv, 2020 BASE Show details 4 Arabic Curriculum Analysis ... The 28th International Conference on Computational Linguistics 2020; Abdelali, Ahmed; Darwish, Kareem. - : Underline Science Inc., 2020 BASE Show details 5 Arabic Diacritic Recovery Using a Feature-Rich biLSTM Model ... Darwish, Kareem; Abdelali, Ahmed; Mubarak, Hamdy. - : arXiv, 2020 BASE Show details 6 Diacritization of Maghrebi Arabic Sub-Dialects ... Abdelali, Ahmed; Attia, Mohammed; Samih, Younes; Darwish, Kareem; Mubarak, Hamdy. - : arXiv, 2018 Abstract: Diacritization process attempt to restore the short vowels in Arabic written text; which typically are omitted. This process is essential for applications such as Text-to-Speech (TTS). While diacritization of Modern Standard Arabic (MSA) still holds the lion share, research on dialectal Arabic (DA) diacritization is very limited. In this paper, we present our contribution and results on the automatic diacritization of two sub-dialects of Maghrebi Arabic, namely Tunisian and Moroccan, using a character-level deep neural network architecture that stacks two bi-LSTM layers over a CRF output layer. The model achieves word error rate of 2.7% and 3.6% for Moroccan and Tunisian respectively and is capable of implicitly identifying the sub-dialect of the input. ... : 6 pages, 3 figures ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.1810.06619 https://arxiv.org/abs/1810.06619 BASE Hide details 7 Arabic Multi-Dialect Segmentation: bi-LSTM-CRF vs. SVM ... Eldesouki, Mohamed; Samih, Younes; Abdelali, Ahmed. - : arXiv, 2017 BASE Show details

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