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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Abdelfatah Maarouf
Sultan Moulay Slimane University

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Automatic translation from English to Amazigh using transformer learning Otman Maarouf; Abdelfatah Maarouf; Rachid El Ayachi; Mohamed Biniz
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i3.pp1924-1934

Abstract

Due to the lack of parallel data, to our knowledge, no study has been conducted on the Amazigh-English language pair, despite the numerous machine translation studies completed between major European language pairs. We decided to utilize the neural machine translation (NMT) method on a parallel corpus of 137,322 sentences. The attention-based encoder-decoder architecture is used to construct statistical machine translation (SMT) models based on Moses, as well as NMT models using long short-term memory (LSTM), gated recurrent units (GRU), and transformers. Various outcomes were obtained for each strategy after several simulations: 80.7% accuracy was achieved using the statistical approach, 85.2% with the GRU model, 87.9% with the LSTM model, and 91.37% with the transformer.
Co-Authors Mohamed Biniz Otman Maarouf Rachid El Ayachi