Evaluation of Gated Recurrent Unit in Arabic Diacritization
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 11
Abstract
Recurrent neural networks are powerful tools giving excellent results in various tasks, including Natural Language Processing tasks. In this paper, we use Gated Recurrent Unit, a recurrent neural network implementing a simple gating mechanism in order to improve the diacritization process of Arabic. Evaluation of Gated Recurrent Unit for diacritization is performed in comparison with the state-of-the art results obtained with Long-Short term memory a powerful RNN architecture giving the best-known results in diacritization. Evaluation covers two performance aspects, Error rate and training runtime.
Authors and Affiliations
Rajae Moumen, Raddouane Chiheb, Rdouan Faizi, Abdellatif EL AFIA
Keywords
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- EP ID EP417677
- DOI 10.14569/IJACSA.2018.091150
- Views 88
- Downloads 0
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