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A Bibliometric Review of Research on Intelligent Personal Assistants: Present Status, Development, and Future Directions


Affiliations
1 Research Scholar, School of Management and Commerce, K.R. Mangalam University, Sohna Road, Gurugram, India
2 Professor, School of Management and Commerce, K.R. Mangalam University, Sohna Road, Gurugram, India
 

Voice assistants based on Artificial Intelligence (AI) are computer programs that use natural language processing (NLP) and machine learning (ML) algorithms to recognize and respond to voice commands and queries in a human-like way. These voice assistants use speech recognition technology to understand spoken commands and questions, process them, and provide relevant responses. The objective of this study is to examine the intellectual framework and effectiveness of voice assistants and to analyze the literature produced by renowned researchers in terms of authors, keywords, and major organizations. This review seeks to offer valuable insights into the growing body of literature on virtual assistants. In this article, the authors have used the bibliometric method to systematically summarize the current state of voice assistant research. They analyzed 563 articles related to Voice assistants from the Scopus database between 2002 and 2023 using the R-Studio ‘Biblioshiny’ tool. The analysis includes an examination of the core journals, articles, authors, institutions, and relevant countries to determine the most influential voice assistants literature. This study also provides a detailed understanding of Co-occurrence network, Co-citation network and Coword analysis. The authors have also used thematic maps to identify the different research topics of voice literature and have grouped them into four clusters, including Motor themes, Niche themes, Emerging themes, and Basic themes. The article concludes by discussing the limitations of the study and highlighting future research directions.

Keywords

Virtual Assistants, Voice Assistants, VBA, Digital Voice Assistant.
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  • A Bibliometric Review of Research on Intelligent Personal Assistants: Present Status, Development, and Future Directions

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Authors

Paramjit Singh
Research Scholar, School of Management and Commerce, K.R. Mangalam University, Sohna Road, Gurugram, India
Ruchika Yadav
Professor, School of Management and Commerce, K.R. Mangalam University, Sohna Road, Gurugram, India

Abstract


Voice assistants based on Artificial Intelligence (AI) are computer programs that use natural language processing (NLP) and machine learning (ML) algorithms to recognize and respond to voice commands and queries in a human-like way. These voice assistants use speech recognition technology to understand spoken commands and questions, process them, and provide relevant responses. The objective of this study is to examine the intellectual framework and effectiveness of voice assistants and to analyze the literature produced by renowned researchers in terms of authors, keywords, and major organizations. This review seeks to offer valuable insights into the growing body of literature on virtual assistants. In this article, the authors have used the bibliometric method to systematically summarize the current state of voice assistant research. They analyzed 563 articles related to Voice assistants from the Scopus database between 2002 and 2023 using the R-Studio ‘Biblioshiny’ tool. The analysis includes an examination of the core journals, articles, authors, institutions, and relevant countries to determine the most influential voice assistants literature. This study also provides a detailed understanding of Co-occurrence network, Co-citation network and Coword analysis. The authors have also used thematic maps to identify the different research topics of voice literature and have grouped them into four clusters, including Motor themes, Niche themes, Emerging themes, and Basic themes. The article concludes by discussing the limitations of the study and highlighting future research directions.

Keywords


Virtual Assistants, Voice Assistants, VBA, Digital Voice Assistant.

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DOI: https://doi.org/10.23862/kiit-parikalpana%2F2023%2Fv19%2Fi2%2F223434