Boosting Arabic Named Entity Recognition Transliteration with Deep Learning

Abstract

The task of transliteration of named entities from one lan- guage into another is complicated and considered as one of the challenging tasks in machine translation (MT). To build a well performed transliteration system, we apply well-es- tablished techniques based on Hybrid Deep Learning. The system based on convolutional neural network (CNN) fol- lowed by Bi-LSTM and CRF. The proposed hybrid mecha- nism is examined on ANERCorp and Kalimat corpus. The results show that the neural machine translation approach can be employed to build efficient machine transliteration systems achieving state-ofthe-art results for Arabic - Eng- lish language.