Nizar Habash, Fadhl Eryani, Salam Khalifa, Owen Rambow, Dana Abdulrahim, Alexander Erdmann, Reem Faraj, Wajdi Zaghouani, Houda Bouamor, Nasser Zalmout, Sara Hassan, Faisal Al-Shargi, Sakhar Alkhereyf, Basma Abdulkareem, Ramy Eskander, Mohammad Salameh, Hind Saddiki
| Challenge: | Existing efforts to conventionalize the dialectal orthography of Arabic have focused on specific dialects and made ad hoc decisions. |
| Approach: | They propose a set of guidelines and meta-guidelines for conventional orthography of Arabic dialects . they apply them to 28 Arab city dialects from Rabat to Muscat . |
| Outcome: | The proposed guidelines and resources are being used by three large Arabic dialect processing projects in three universities. |
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| Challenge: | Arabic dialects are non-standard varieties of Arabic commonly spoken across the Arab world, but lack standard orthographies. |
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| Challenge: | Existing work on Arabic Dialect Identification typically targeted coarse-grained five dialect classes plus Standard Arabic at most (6-way classification). |
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Beyond Orthography: Automatic Recovery of Short Vowels and Dialectal Sounds in Arabic (2024.acl-long)
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The MADAR Arabic Dialect Corpus and Lexicon (L18-1)
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Houda Bouamor, Nizar Habash, Mohammad Salameh, Wajdi Zaghouani, Owen Rambow, Dana Abdulrahim, Ossama Obeid, Salam Khalifa, Fadhl Eryani, Alexander Erdmann, Kemal Oflazer
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AraBench: Benchmarking Dialectal Arabic-English Machine Translation (2020.coling-main)
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| Challenge: | Existing efforts to translate Arabic dialects to English are limited due to the lack of evaluation benchmarks. |
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You Tweet What You Speak: A City-Level Dataset of Arabic Dialects (L18-1)
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