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

• Published in: Multimedia tools and applications Vol. 82; no. 3; pp. 3713 - 3744
• Main Authors: Khurana, Diksha, Koli, Aditya, Khatter, Kiran, Singh, Sukhdev
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.01.2023; Springer Nature B.V
• Subjects: Alliances; Automatic summarization; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Datasets; Discourse analysis; Information retrieval; Language; Linguistics; Machine translation; Morphology; Multimedia; Multimedia Information Systems; Natural language generation; Natural language processing; Phonology; Semantics; Sound; Special Purpose and Application-Based Systems; Speech; Speech recognition; Syntax; Trends; NLP applications; NLP evaluation metrics; Natural language processing; Natural language generation; Natural language understanding
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-022-13428-4

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 N atural L anguage G eneration 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.