Cited by 1,823Natural Language Processing TechniquesTopic ModelingSpeech and dialogue systems

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

Open access
Khurana, Diksha, Koli, Aditya, Khatter, Kiran, Singh, Sukhdev·2023·Multimedia Tools and Applications

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 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.

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  • Intrinsic evaluation metrics solely rely on surface-form similarity and language-specific perspectives, rendering them inadequate for healthcare chatbots.

    “However, they solely rely on surface-form similarity and language-specific perspectives, rendering them inadequate for healthcare chatbots.”
  • Intrinsic metrics lack the capability to capture semantics, context, distant dependencies, semantically critical ordering change, and human perspectives, particularly in real-world scenarios.

    “These metrics lack the capability to capture essential elements such as semantics19,20, context19,21, distant dependencies22,23, semantically critical ordering change21, and human perspectives, particularly in real-world scenarios.”

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Authors
Khurana, D., Koli, A., Khatter, K., & Singh, S.
Affiliations
  • Manav Rachna International Institute of Research and Studies (IN)
  • BML Munjal University (IN)
  • Amity University (IN)
Corresponding author
Khatter, Kiran
Venue
Multimedia Tools and Applications
Published
2022-07-14
Volume
82
Issue
3
Pages
3713-3744
ISSN
  • 1380-7501 (ISSN-L)
  • 1573-7721
OpenAlex
W2747680751
Cited by
1,823
References
152
Citations by year
2026: 251 · 2025: 583 · 2024: 560 · 2023: 301 · 2022: 50 · 2021: 48 · 2020: 22 · 2019: 4 · 2018: 3
FWCI
122.91
Type
journal article
Language
en
Open access
Locations
  • Multimedia Tools and Applications (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
  • Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
  • Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
Keywords
natural language processing, machine translation, email spam detection, information extraction, text summarization, question answering, natural language generation, history of NLP, NLP datasets

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