A Study on Natural Language Processing: Bridging the Gap Between Human Communication and Machine Understanding

Abstract

Natural Language Processing (NLP) represents a significant intersection between human language and machine understanding, enabling computers to interpret, generate, and respond to human communication in a meaningful way. This paper explores the foundational principles of NLP, examining the linguistic, computational, and algorithmic aspects that contribute to its functionality. It discusses various machine learning techniques, including supervised, unsupervised, and reinforcement learning, as well as the transformative impact of deep learning architectures such as transformers on NLP applications.