КОНФЕРЕНЦІЇ ВНТУ електронні наукові видання, 
Молодь в науці: дослідження, проблеми, перспективи (МН-2026)

Розмір шрифта: 
NATURAL LANGUAGE PROCESSING ARCHITECTURES FOR CONTEXTUAL ERROR DETECTION IN ENGLISH ACADEMIC WRITING
Світлана Юріївна Підопригора, Вікторія Володимирівна Чопляк

Остання редакція: 2026-05-26

Анотація


The paper investigates the implementation of Natural Language Processing (NLP) technologies for automated error detection in English academic discourse. While traditional rule-based algorithms are limited to basic syntactic and lexical corrections, modern transformer-based architectures allow for deep semantic analysis and contextual disambiguation. This study explores the theoretical transition from heuristic spell-checkers to advanced neural networks capable of understanding English linguistic nuances. The research highlights how these computational tools enhance the quality of academic writing for non-native speakers by identifying complex contextual anomalies.

Ключові слова


natural language processing; English academic writing; contextual error detection; transformer architectures; computational linguistics

Посилання


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