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. 2023;82(3):3713-3744.
doi: 10.1007/s11042-022-13428-4. Epub 2022 Jul 14.

Natural language processing: state of the art, current trends and challenges

Diksha Khurana  1 , Aditya Koli  1 , Kiran Khatter  2 , Sukhdev Singh  3
Affiliations

Natural language processing: state of the art, current trends and challenges

Diksha Khurana et al. Multimed Tools Appl. 2023.

Abstract

Natural language processing (NLP) has recently gained much attention for representing and analyzing human language computationally. It has spread its applications in various fields such as machine translation, email spam detection, information extraction, summarization, medical, and question answering etc. In this paper, we first distinguish four phases by discussing different levels of NLP and components of Natural Language Generation followed by presenting the history and evolution of NLP. We then discuss in detail the state of the art presenting the various applications of NLP, current trends, and challenges. Finally, we present a discussion on some available datasets, models, and evaluation metrics in NLP.

Keywords: NLP applications; NLP evaluation metrics; Natural language generation; Natural language processing; Natural language understanding.

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Conflict of interest statement

Conflict of interestThe first draft of this paper was written under the supervision of Dr. Kiran Khatter and Dr. Sukhdev Singh, associated with CL- Educate: Accendere Knowledge Management Services Pvt. Ltd. and deputed at the Manav Rachna International University. The draft is also available on arxiv.org at https://arxiv.org/abs/1708.05148

Figures

Fig. 1
Fig. 1
Broad classification of NLP
Fig. 2
Fig. 2
Components of NLG
Fig. 3
Fig. 3
A walkthrough of recent developments in NLP
See this image and copyright information in PMC

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