Abstract
This paper focuses on identifying the Arabic Language 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 ngrams 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.
| Original language | English |
|---|---|
| Pages (from-to) | 620-627 |
| Number of pages | 8 |
| Journal | International Journal of Advanced Computer Science and Applications |
| Volume | 11 |
| Issue number | 5 |
| DOIs | |
| State | Published - 2020 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2020 Science and Information Organization.
Keywords
- Arabic
- Deep learning
- Gated recurrent unit network (GRUN)
- Native language identification (NLI)
ASJC Scopus subject areas
- General Computer Science