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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.