Natural Language Processing: History, Evolution, Application and Future Work

EasyChair Preprint 3239

Abstract

It is quite hard to imagine a smart system like a voice assistant or a chat-bot or a recommender system without Natural Language Processing (NLP). It all starts with an initial unit that first interprets the data (audio or text) provided and then starts making sense of the data and after proper processing of the data the actual steps are followed by the machine to throw some replies or get the work done. NLP does not fall under a discipline; rather it is a part of several different disciplines i.e. computer science, information engineering, Artificial Intelligence (AI), and linguistics. The concern of NLP is the interaction between a computer and human languages. NLP areas include Speech Recognition, Machine Translation, Automatic Text Summarization, Part-of-Speech Tagging, etc. Generally, NLP is used in many real-time applications like smart homes, smart offices like Alexa, Cortana, Siri, and Google Assistant. The history of NLP generally started in the 1950s and has come a long way from then and improved a lot. This paper discusses the history of NLP, its evolution, its tools and techniques, and its applications in different fields. The paper also discusses the role of Machine Learning and Artificial Neural Networks (ANNs) to improve NLP.

Keyphrases: ANNs, ATNs, NLP, deep learning, machine learning

@booklet{EasyChair:3239,
  author    = {Prashant Johri and Mukul Kathait and Munish Sabharwal and Ahmad T. Al-Taani and Shakhzod Suvanov},
  title     = {Natural Language Processing: History, Evolution, Application and Future Work},
  howpublished = {EasyChair Preprint 3239},
  year      = {EasyChair, 2020}}