ARTIFICAL INTELIGENCE MODELS IN LINGUISTIC RESEARCH, CHALENGIES AND OPPORTUNITIES

Tinatin Mshvidobadze

Tinatin Mshvidobadze Doctor of Technical Sciences Associate Professor of Gori State University Gori, Chavchavadze st. #53, 1400, Georgia http://orcid.org/0000-0003-3721-9252

Abstract

Artificial Intelligence (AI) has emerged as a transformative force in linguistic research, offering innovative methodologies and tools for language learning and analysis. This paper provides a comprehensive overview of the potential of AI in linguistic research, with a particular focus on its role in language analysis.

By describing natural language processing (NLP), machine learning (ML), and deep learning (DL) techniques, this paper explores the role of AI in linguistic phenomena in our consciousness.

While AI has revolutionized linguistic research, it also addresses challenges such as the relationship to annotated data, biases in AI models, and ethical considerations.

To address these challenges, two AI technologies are worth considering: computer vision (CV) and natural language processing (NLP). Computer vision can identify text, refine data, and analyze images. NLP translates and interprets multilingual texts.

This paper explores the potential and challenges of using AI technologies in linguistic landscape (LL) research and discusses methods for improving data collection.

Keywords: artificial intelligence, linguistic research, natural language processing, computer vision, language models, machine learning.