Neural Machine Translation: Basic Principles, Strengths and Weaknesses
Ескіз недоступний
Дата
2023
Науковий керівник
Назва журналу
Номер ISSN
Назва тому
Видавець
DeSympProMonograph
Анотація
The basic principles of Neural machine translation (NMT) involve the use of artificial neural networks to transform text from one language to another. The networks are trained on large bilingual cprpora to learn the statistical patterns and structures of both languages. In spite of a high speed of the translation process, NMT has also substantial drawbacks. They include the following: NMT models require large amounts of data and rely on the availability of parallel data required for training these models.
Опис
Ключові слова
Neural machine translation (NMT), NMT translation model, bilingual corpora
Бібліографічний опис
Shevchenko, O. M. Neural Machine Translation: Basic Principles, Strengths and Weaknesses // Shevchenko O. M., Ogurtsova O. L. // Monographic series «European Science». – 2023. – Book 18, Part 4. – P. 86-92.