SUAR: Towards Building a Corpus for the Saudi Dialect
Nora Al-Twairesh, Rawan N. Al-Matham, Nora Madi, Nada Almugren, Al-Hanouf Al-Aljmi, Shahad Alshalan, Raghad Alshalan, Nafla Alrumayyan, Shams Al-Manea, Sumayah Bawazeer, Nourah Almutlaq, Nada Almanea, Waad Bin Huwaymil, Dalal Alqusair, Reem Alotaibi, Suha Al-Senaydi, Abeer Alfutamani · Procedia Computer Science · 2018
This paper presents the preliminary results of the construction of a morphologically annotated corpus for the Saudi dialect. We call the corpus SUAR (SaUdi corpus for NLP Applications and Resources). The corpus consists of around 104,079 words collected from different online sources. The linguistic features of the Saudi dialect are elaborated and compared with Modern Standard Arabic and other Arabic dialects. This paper conducts a pilot study to explore possible directions to facilitate the morphological annotation of the Saudi corpus. The corpus was automatically annotated using the MADAMIRA tool, after which it was manually inspected to validate the resulting analysis.