Human Language Processing: Mechanisms, Techniques, And Principles

Abstract

This research addresses the pivotal and complementary relationship between Artificial Intelligence (AI) and human language, emphasizing the paramount importance of Natural Language Processing (NLP) techniques. NLP acts as a crucial bridge, enabling computer systems to understand and analyze human text and speech across multiple levels (syntactic, semantic, and pragmatic). The paper reviews the historical development of AI technologies in this domain—from rule-based methodologies to the revolution of Deep Learning and Large Language Models (LLMs)—clarifying the theoretical foundations upon which machine comprehension is built. Furthermore, it highlights the essential practical applications of NLP, such as machine translation, conversational analysis, sentiment extraction, and data retrieval. The research concludes by discussing existing challenges (like linguistic ambiguity and dialect variation) and outlining the future opportunities