Abstract: This paper proposes a comprehensive review on current developments in the area of Natural Language Processing (NLP), covering a wide variety of methodologies and technologies, including sentiment analysis, machine learning (ML) approaches, chatbots along with speech recognition approaches. The paper is designed to support both commoners and technically skilled personnel to understand the fundamentals of traditional and advanced NLP methods. The authors provide a comprehensive survey of previous literature in NLP technologies from the year 2013 to 2023 to understand the current state of affairs. While few parts of the work might have been roofed in additional depth, yet an in-depth current exploration of the approaches might have to be considered. Nevertheless, this paper is still a valued resource for investigators and researchers in the field of NLP.

Key words: Natural Language Processing (NLP), Text data, Literature review, Machine Learning (ML)

| DOI: 10.17148/IARJSET.2024.11438