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Romanized Arabic and Berber detection using prediction by partial matching and dictionary methods.

, , and . AICCSA, page 1-7. IEEE Computer Society, (2016)

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Identifying Sentiments in Algerian Code-switched User-generated Comments., , and . LREC, page 2698-2705. European Language Resources Association, (2020)Romanized Berber and Romanized Arabic Automatic Language Identification Using Machine Learning., , and . VarDial@COLING, page 53-61. The COLING 2016 Organizing Committee, (2016)Neural Models for Detecting Binary Semantic Textual Similarity for Algerian and MSA., , and . WANLP@ACL 2019, page 78-87. Association for Computational Linguistics, (2019)Identification of Languages in Algerian Arabic Multilingual Documents., and . WANLP@EACL, page 1-8. Association for Computational Linguistics, (2017)Romanized Arabic and Berber detection using prediction by partial matching and dictionary methods., , and . AICCSA, page 1-7. IEEE Computer Society, (2016)Gulf Arabic Linguistic Resource Building for Sentiment Analysis., and . LREC, European Language Resources Association (ELRA), (2016)Automatic Detection of Arabicized Berber and Arabic Varieties., , , and . VarDial@COLING, page 63-72. The COLING 2016 Organizing Committee, (2016)Normalising Non-standardised Orthography in Algerian Code-switched User-generated Data., , and . W-NUT@EMNLP, page 131-140. Association for Computational Linguistics, (2019)ASIREM Participation at the Discriminating Similar Languages Shared Task 2016., , and . VarDial@COLING, page 163-169. The COLING 2016 Organizing Committee, (2016)When is Multi-task Learning Beneficial for Low-Resource Noisy Code-switched User-generated Algerian Texts?, and . CodeSwitch@LREC, page 17-25. European Language Resources Association, (2020)