Boosting Arabic Named Entity Recognition Transliteration with Deep Learning
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...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | |
| منشور في: |
2020
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| الوصول للمادة أونلاين: | https://bspace.buid.ac.ae/handle/1234/3066 |
| الوسوم: |
إضافة وسم
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| الملخص: | 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. |
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