Natural Language Processing (NLP) for Multilingual Analysis

Abstract

This paper explores the application of Natural Language Processing (NLP) techniques for multilingual analysis, addressing the challenges and methodologies involved in processing and analyzing text across diverse languages. It reviews recent advancements in language models, data preprocessing, and system architectures that facilitate effective multilingual understanding. The study proposes a comprehensive framework and evaluates its performance using benchmark datasets, demonstrating improvements in accuracy for multilingual text processing tasks. The results underscore the potential impact of such systems on enhancing global communication, information retrieval, and machine translation services.