Neural networks in machine translation

Автор: Dukalskaya I.V., Barakovskaya E.V.

Журнал: Инфокоммуникационные технологии @ikt-psuti

Рубрика: Новые информационные технологии

Статья в выпуске: 2 т.20, 2022 года.

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The article presents the main development stages of the machine translation and the principles of neurolinguistics that can be used for translating tools. Some assumptions about whether neural networks are capable of performing simulation are provided. It is considered how the GLOM theory can change the field of machine translation in future. The purpose is to explore neural networks in the field of machine translation, consider the prospect of their further development and derive principles that will allow neural networks to simulate neurolinguistic processes.This purpose is going to be achieved through the following actions: the analysis of various approaches to machine translation along withneurolinguistics processes in the human brain. Based on the data collected, principles of neural network design are determined. The authors make assumptions about the development of neural networks based on the GLOM.

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Machine translation, neurolinguistics, neural networks, artificial intelligence

Короткий адрес: https://sciup.org/140296731

IDR: 140296731   |   DOI: 10.18469/ikt.2022.20.2.10

Статья научная