THE ROLE OF ARTIFICIAL INTELLIGENCE AND DIGITAL CORPORA IN MODERN LINGUISTIC RESEARCH: OPPORTUNITIES AND CHALLENGES
https://doi.org/10.5281/zenodo.20377418
Kalit so‘zlar
Artificial Intelligence, Natural Language Processing, Corpus Linguistics, Linguistic Modeling, Machine Learning, Deep Learning, Word Embedding, Transformer Model, BERT.Annotasiya
This article analyzes the role of artificial intelligence, digital corpora, and linguistic modeling in modern linguistic research. It examines the development of linguistic approaches, starting from traditional theories, particularly those proposed by Chomsky, to contemporary methods based on artificial intelligence. In particular, the effectiveness of technologies such as Natural Language Processing (NLP), machine learning, and deep learning in language analysis is discussed. The article also describes linguistic modeling processes using modern models such as Word2Vec, Transformer, and BERT, and highlights their advantages in processing large amounts of textual data. In addition, special attention is given to the importance of digital corpora in developing empirical research in linguistics.
However, the limitations of artificial intelligence technologies are also considered from a critical perspective. Issues such as the problem of “understanding” language, dependence on data, model bias, and ethical concerns are discussed. These aspects show that, along with its significant potential, artificial intelligence also has certain limitations in linguistic research.
The results of the study indicate that artificial intelligence and digital corpora are taking linguistics to a new level. However, their effective use requires a critical approach and scientifically grounded integration. In this article, the author analyzes existing approaches, compares their advantages and disadvantages, and presents several suggestions for more effective use of artificial intelligence in linguistic research.
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