(untitled) (Proceedings of International Conference on Educational Discoveries and Humanities, 2024)
A machine translation technique called neural machine translation (NMT) uses artificial neural networks to predict the probability of word sequences. Typically, it incorporates all sentence models into one integrated model. This is the dominant approach today[1, 2] and under certain conditions can produce translations that compete with human translations when translating between languages with few resources[3]. However, especially in languages where high-quality data is less available[1, 4, 5] and there are still problems with domain switching between the data the system is trained on and the text to be translated. available[1]. NMT systems also tend to produce literal translations[5].