Title: Artificial Intelligence in Legal Linguistics: Analysing and Translating Legal Terms in Multilingual Legal Discourse
Authors: Khujakulov Sunnatullo
Volume: 9
Issue: 12
Pages: 5-10
Publication Date: 2025/12/28
Abstract:
The complexity of legal language poses significant challenges for accurate analysis and translation across multilingual legal systems. Legal terms often carry precise semantic, cultural, and procedural nuances that are difficult to convey using conventional translation or manual analysis methods. This paper explores the role of Artificial Intelligence (AI) in legal linguistics, focusing on the analysis and translation of legal terminology in multilingual legal discourse. By integrating Natural Language Processing (NLP) techniques, machine learning algorithms, and ontology-based frameworks, AI can identify, disambiguate, and contextualize legal terms more efficiently than traditional approaches. The study examines current AI applications, including neural machine translation, transformer-based language models, and semantic similarity analysis, highlighting their effectiveness in maintaining terminological consistency and cross-lingual equivalence. Case studies demonstrate AI's potential in translating complex legal texts, such as statutes, contracts, and court decisions, while also identifying limitations, including domain-specific ambiguity and training data bias. The paper emphasizes a hybrid approach, combining AI-assisted analysis with expert human validation, to ensure accuracy and reliability. Findings suggest that AI significantly enhances the efficiency, scalability, and semantic precision of legal term analysis and translation, offering promising directions for advancing multilingual legal communication, cross-border legal practice, and comparative law studies.