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Translation System from Saudi Dialect to Modern Standard Arabic Using Deep Learning Techniques

  • Nehad M. Ibrahim,
  • Afifa Alawami,
  • Ayat Alokaily,
  • Fatimah Alturaiki,
  • Quds Alhelal,
  • Shadha Binagag,
  • Khadeejah Rasheed Alhindi,
  • Duaa Ali A. L. Kubaisy

摘要

The evolution of cultures and societies worldwide has led to the rise of various languages and dialects, which differ based on their geographic location. In this paper, a framework for translating the Saudi dialect into Modern Standard Arabic using deep learning techniques was proposed. In the study, two datasets were used. One is the Gulf dataset, and the other is the Saudi dataset. Two experiments were conducted using the datasets. The LSTM model achieved an accuracy of 88% using Gulf dataset and 90% using Saudi dataset. Similarly, the BI-LSTM model achieved an accuracy of 92% with Gulf dataset and 95% with Saudi dataset. In conclusion, the study proposes a framework for translating Saudi dialect to MSA using deep learning models.