Deep Learning Model for Identifying the Arabic Language Learners based on Gated Recurrent Unit Network
Seifeddine Mechti, Roobaea Alroobaea, Moez Krichen, Saeed Rubaiee, Anas Ahmed · International Journal of Advanced Computer Science and Applications · 2020
This paper focuses on identifying the Arabic Lan-guage learners. The main contribution of the proposed method is to use a deep learning model based on the Gated Recurrent Unit Network (GRUN). The proposed model explores a multitude of stylistic features such as the syntax, the lexical and the n-grams ones. To the best of our awareness, the obtained results outperform those obtained by the best existing systems. Our accuracy is the best comparing with the pioneers (45% vs 41%), considering the limited data and the unavailability of accurate tools dedicated to the Arabic language.