@inproceedings{fashwan-alansary-2017-shakkil,
    title = "{SHAKKIL}: An Automatic Diacritization System for {M}odern {S}tandard {A}rabic Texts",
    author = "Fashwan, Amany  and
      Alansary, Sameh",
    editor = "Habash, Nizar  and
      Diab, Mona  and
      Darwish, Kareem  and
      El-Hajj, Wassim  and
      Al-Khalifa, Hend  and
      Bouamor, Houda  and
      Tomeh, Nadi  and
      El-Haj, Mahmoud  and
      Zaghouani, Wajdi",
    booktitle = "Proceedings of the Third {A}rabic Natural Language Processing Workshop",
    month = apr,
    year = "2017",
    address = "Valencia, Spain",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/W17-1311/",
    doi = "10.18653/v1/W17-1311",
    pages = "84--93",
    abstract = "This paper sheds light on a system that would be able to diacritize Arabic texts automatically (SHAKKIL). In this system, the diacritization problem will be handled through two levels; morphological and syntactic processing levels. The adopted morphological disambiguation algorithm depends on four layers; Uni-morphological form layer, rule-based morphological disambiguation layer, statistical-based disambiguation layer and Out Of Vocabulary (OOV) layer. The adopted syntactic disambiguation algorithms is concerned with detecting the case ending diacritics depending on a rule based approach simulating the shallow parsing technique. This will be achieved using an annotated corpus for extracting the Arabic linguistic rules, building the language models and testing the system output. This system is considered as a good trial of the interaction between rule-based approach and statistical approach, where the rules can help the statistics in detecting the right diacritization and vice versa. At this point, the morphological Word Error Rate (WER) is 4.56{\%} while the morphological Diacritic Error Rate (DER) is 1.88{\%} and the syntactic WER is 9.36{\%}. The best WER is 14.78{\%} compared to the best-published results, of (Abandah, 2015); 11.68{\%}, (Rashwan, et al., 2015); 12.90{\%} and (Metwally, Rashwan, {\&} Atiya, 2016); 13.70{\%}."
}