إطار عام يعتمد على التعلم العميق للترجمة الرقمية من العربية إلى الإنجليزية | ||||
| المجلة العلمية لكلية التربية النوعية جامعة دمياط | ||||
| Volume 2024, Issue 9, June 2024, Page 1-19 PDF (1.67 MB) | ||||
| Document Type: البحوث العلمية الأصيلة | ||||
| DOI: 10.21608/sjeud.2023.243711.1015 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Asmaa Bialy   1; Elsaeed AbdElrazek 2; Doaa Hawa 3
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| 1Damietta University Faculty of Specific Education Computer Department | ||||
| 2Damietta University, Faculty of Specific Education, , Computer Department | ||||
| 3Damietta University, Faculty of Specific Education, Computer Department | ||||
| Abstract | ||||
| This paper focuses on NMT systems, NMT is developed with deep learning techniques; it’s kind of MT attempts to build and train a single, large neural network that reads a sentence and outputs a correct translation. So, we proposed a system on based NMT systems for the translation of Arabic texts into English, This system is for translating texts in the computer field, The proposed system contains five main stages , the system is contains in a database containing a bilingual dictionary (Arabic-English) containing terms in the field of Computer-based, this system based on the encoder-decoder by RNN model in which the encoder reads and encodes the source sentence into a fixed-length vector while the decoder produces a translation output from the encoded vector, the system was evaluated by human experts , addition to using the blue scale, The final results proved that the proposed method achieved higher performance than other systems. | ||||
| Keywords | ||||
| Machine translation; NMT systems; Arabic machine translation | ||||
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