Abstract
In this digital era, Natural language Processing is not just a computational process rather it is a way to communicate with machines as humanlike. It has been used in several fields from smart artificial assistants to health or emotion analyzers. Imagine a digital era without Natural language processing is something which we cannot even think of. In Natural language Processing, firstly it reads the information given and after that begins making sense of the information. After the data has been properly processed, the real steps are taken by the machine throwing some responses or completing the work. In this paper, I review the journey of natural language processing from the late 1940s to the present. This paper also contains several salient and most important works in this timeline which leads us to where we currently stand in this field. The review separates four eras in the history of Natural language Processing, each marked by a focus on machine translation, artificial intelligence impact, the adoption of a logico-grammatical style, and an attack on huge linguistic data. This paper helps to understand the historical aspects of Natural language processing and also inspires others to work and research in this domain.
Highlights
Computer technology dominates a wide range of sectors, from our daily lives to advanced scientific techniques
Several failures and lack of proper machines could not stop the progress of Natural Language Processing (NLP) research
Natural language processing is used by most Artificial Intelligence (AI) systems today, including Google Assistant, Netflix, Apple's Siri, and Grammarly
Summary
Computer technology dominates a wide range of sectors, from our daily lives to advanced scientific techniques. We've made a lot of progress in AI Technology, and life will be impossible without this These results were achieved because of the ongoing efforts of AI researchers. After Siri, Google integrated “Google Assistant”, a voice assistant to the operating system Android This is the groundbreaking achievement of NLP. These voice assistants are as good as a human. It is all happening because of the advanced research in NLP, AI, and Deep Learning. NLP researchers have been improved a lot because of highperformance computers by which we can perform a lot of complex calculations, a steady increase of data and potential, and good algorithms. The last section discusses the conclusion in NLP research and the future refinements
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