Abstract
Recently, artificial intelligence-based machine translation has been much improved over the traditional methods. A machine translator is very useful for translating text or speech from one language to another. Machine translators have replaced the word mechanism in one language for words in another with verbatim translations. However, a good translation should be employed a both a sentence and a word that have complete meaning in accordance with the context of relevant sentence. In this paper, we studied on English – Vietnamese translation using deep learning methods including Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Units (GRU), Attention, and Transformer. The deep learning-based machine translators were compared based on the test accuracy of results translation. It was found that best deep learning-based machine translator model was the Attention mechanism, achieving 98.8% accuracy. The Transformer yielded second rank or 98.5% accuracy.
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Minh, T.N., Meesad, P., Nguyen Ha, H.C. (2021). English-Vietnamese Machine Translation Using Deep Learning. In: Meesad, P., Sodsee, D.S., Jitsakul, W., Tangwannawit, S. (eds) Recent Advances in Information and Communication Technology 2021. IC2IT 2021. Lecture Notes in Networks and Systems, vol 251. Springer, Cham. https://doi.org/10.1007/978-3-030-79757-7_10
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DOI: https://doi.org/10.1007/978-3-030-79757-7_10
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