Corpus linguistics and deep learning

Abstract

Natural language processing (NLP) has seen significant progress in the last decade thanks to deep learning methods. Corpus linguistics, as a discipline that studies language patterns through large text databases, has become an indispensable part of the development of artificial intelligence. This paper explores the connection between corpus linguistics and deep learning methods, with particular emphasis on transformer models such as BERT and GPT. The goal of the research is to analyze the effectiveness of different NLP models, to point out their advantages and limitations, and to propose guidelines for further development in the field of language processing.

Keywords

corpus linguistics, deep learning, natural language processing, neural networks, NLP, artificial intelligence