Natural Language Processing: An Approach to Aid Emergency Services in COVID-19 Pandemic

Abstract

In the recent years, Natural Language  Processing (NLP) has been widely adopted in numerous  applications to organize and structure knowledge to  accomplish tasks like translation, summarization, named  entity recognition, relationship extraction and speech  recognition. With the advent of deep learning techniques,  there has been significant increase in the processing  efficiency of NLP based systems. The COVID-19  pandemic situation has challenged the medical research,  IT operations, business processes and world economy at  large. Numerous solutions are being developed to make  lockdown and social distancing successful without  causing much inconvenience to public. The current trends  and applications of NLP can act as a critical support  system for fighting COVID-19 pandemic situation. This  paper presents a comparative assessment of various deep  learning models for NLP techniques and proposes an NLP  framework to develop essential and emergency services  support system to minimize human interactions.