Manuscript Number : CSEIT217698

Trends In Natural Language Processing : Scope And Challenges

Authors(2) :-Shreyashi Chowdhury, Asoke Nath

Natural language processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyse large amounts of natural language data. The goal is a computer capable of "understanding" the contents of documents, including the contextual nuances of the language within them.NLP combines computational linguistics—rule-based modelling of human language—with statistical, machine learning, and deep learning models. Together, these technologies enable computers to process human language in the form of text or voice data and to ‘understand’ its full meaning, complete with the speaker or writer’s intent and sentiment. Challenges in natural language processing frequently involve speech recognition, natural language understanding, and natural language generation. This paper discusses on the various scope and challenges , current trends and future scopes of Natural Language Processing.

Authors and Affiliations

Shreyashi Chowdhury
Computer Science, St. Xavier's College, Kolkata, West Bengal, India
Asoke Nath
Computer Science, St. Xavier's College, Kolkata, West Bengal, India

Natural Language processing, Artificial Intelligence, Computer Linguistics, Speech Recognition, Natural Language Generation.

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Publication Details

Published in : Volume 7 | Issue 6 | November-December 2021
Date of Publication : 2021-12-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 393-401
Manuscript Number : CSEIT217698
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Shreyashi Chowdhury, Asoke Nath, "Trends In Natural Language Processing : Scope And Challenges ", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 7, Issue 6, pp.393-401, November-December-2021. Available at doi : https://doi.org/10.32628/CSEIT217698
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