IJIRCST

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

Komal | Akshay Sharma

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.

NLP, NLG, deep learning, artificial intelligence, name entity recognition, machine translation, COVID-19.

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[Komal , Akshay Sharma (2020) Natural Language Processing: An Approach to Aid Emergency Services in COVID-19 Pandemic IJIRCST Vol-8 Issue-3 Page No-213-217] (ISSN 2347 - 5552). www.ijircst.org

Komal

Assistant Professor, Department of Computer Science and Engineering, Amity University Haryana, Gurugram, India (email: komal.sang@gmail.com)