Skip to main content
SpringerLink
Log in
Book cover

International Conference on Human-Computer Interaction

HCII 2022: Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Health, Operations Management, and Design pp 443–455Cite as

A Bibliometric Analysis of Intelligent Voice Interaction Based on VOSviewer

  • Conference paper
  • First Online:

  • 1164 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13320))

Abstract

VOSviewer was used as an analysis tool to sort out and analyze intelligent voice interaction. The time span was set as five years, and 12,558 results were searched in total. The database was screened by the types of papers in WOS core journal sets, and 2687 records were refined. Word frequency statistics and keyword clustering method based on author and country relationship were used to construct the atlas, and the clustering results were displayed intuitively by VOSviewer. The results show that the current studies of voice interaction mostly take behavioral experiments. Keywords of voice interaction include voice, recognition, perception, health, knowledge education, social participation, information retrieval, human-computer interface. Based on human-computer interaction research, artificial intelligence, behavior, gender keywords becomes new research trend in recent years. In the study of author distribution, Munteanu, Cosmin Clark, Leigh, Torre and Ilaria are the authors as the core, showing scattering pattern, and the correlation among authors is not very close. From the perspective of national branches, European and American regions led by the United States are the first to initiate research. In recent years, China, Spain, Australia and other countries have also emerged in the field of research.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   59.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   79.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Schnabel, E.-L., Wahl, H.-W., Schönstein, A., Frey, L., Draeger, L.: Nurses’ emotional tone toward older inpatients: do cognitive impairment and acute hospital setting matter? Eur. J. Ageing 17(3), 371–381 (2019). https://doi.org/10.1007/s10433-019-00531-z

    Article  Google Scholar 

  2. Lu, J.X., Wang, P., Shi, H.Z., Wang, X.: Study on multichannel speech enhancement technology in voice human-computer interaction. In: Advanced Materials Research, vol. 267, pp. 762–767. Trans Tech Publications Ltd (2011)

    Google Scholar 

  3. Kumah-Crystal Yaa, A., Pirtle Claude, J., Whyte Harrison, M., Goode Edward, S., Anders Shilo, H., Lehmann Christoph, U.: Electronic health record interactions through voice: a review. Appl. Clin. Inform. 9(3), 541–552 (2018). https://doi.org/10.1055/s-0038-1666844

    Article  Google Scholar 

  4. Huang, Z., Huang, X.: A study on the application of voice interaction in automotive human machine interface experience design. In: AIP Conference Proceedings, vol. 1955, no. 1, p. 040074. AIP Publishing LLC (2018)

    Google Scholar 

  5. Aeschlimann, S., Bleiker, M., Wechner, M., Gampe, A.: Communicative and social consequences of interactions with voice assistants. Comput. Hum. Behav. 112, 106466 (2020)

    Article  Google Scholar 

  6. Filimon, M., Iftene, A., Trandabăţ, D.: Bob-a general culture game with voice interaction. Procedia Comput. Sci. 159, 323–332 (2019)

    Article  Google Scholar 

  7. Yang, L., Sobolev, M., Tsangouri, C., Estrin, D.: Understanding user interactions with podcast recommendations delivered via voice. In: Proceedings of the 12th ACM Conference on Recommender Systems, pp. 190–194 (2018)

    Google Scholar 

  8. Jones, V.K., Hanus, M., Yan, C., Shade, M.Y., Boron, J.B., Bicudo, R.M.: Reducing loneliness among aging adults: the roles of personal voice assistants and anthropomorphic interactions. Front. Public Health 9 (2021)

    Google Scholar 

  9. Bülthoff, I., Newell, F.N.: Crossmodal priming of unfamiliar faces supports early interactions between voices and faces in person perception. Vis. Cogn. 25(4–6), 611–628 (2017)

    Article  Google Scholar 

  10. Coffey, F., Tsuchiya, K., Timmons, S., Baxendale, B., Adolphs, S., Atkins, S.: Analysing voice quality and pitch in interactions of emergency care simulation. BMJ Simul. Technol. Enhanced Learn. 4(4), 196 (2018)

    Article  Google Scholar 

  11. Huang, K.L., Duan, S.F., Lyu, X.: Affective voice interaction and artificial intelligence: a research study on the acoustic features of gender and the emotional states of the PAD model. Front. Psychol. 12, 1212 (2021)

    Google Scholar 

  12. Schelinski, S., Roswandowitz, C., von Kriegstein, K.: Voice identity processing in autism spectrum disorder. Autism Res. 10(1), 155–168 (2017)

    Article  Google Scholar 

  13. Chen, M., Zhou, P., Fortino, G.: Emotion communication system. IEEE Access 5, 326–337 (2016)

    Article  Google Scholar 

  14. Zikang, L., Guizhi, X., Miaomiao, G.: Design and research of audio-visual fusion blind guiding robot. Laser Optoelectron. Prog. 54(12), 121506 (2017)

    Article  Google Scholar 

  15. Hodges-Simeon, C.R., Gaulin, S.J., Puts, D.A.: Different vocal parameters predict perceptions of dominance and attractiveness. Hum. Nat. 21(4), 406–427 (2010). https://doi.org/10.1007/s12110-010-9101-5

    Article  Google Scholar 

  16. Lutfi, S.L., Fernández-Martínez, F., Lucas-Cuesta, J.M., Lopez-Lebon, L., Montero, J.M.: A satisfaction-based model for affect recognition from conversational features in spoken dialog systems. Speech Commun. 55(7–8), 825–840 (2013)

    Article  Google Scholar 

  17. Poushneh, A.: Humanizing voice assistant: the impact of voice assistant personality on consumers’ attitudes and behaviors. J. Retail. Consum. Serv. 58, 102283 (2021)

    Article  Google Scholar 

  18. Murad, C., Munteanu, C.: “I don’t know what you’re talking about, HALexa” the case for voice user interface guidelines. In: Proceedings of the 1st International Conference on Conversational User Interfaces, pp. 1–3 (2019)

    Google Scholar 

  19. Kaye, J.J., et al.: Panel: voice assistants, UX design and research. In: Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems, pp. 1–5 (2018)

    Google Scholar 

  20. Clark, L., et al.: What makes a good conversation? Challenges in designing truly conversational agents. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 1–12 (2019)

    Google Scholar 

  21. Porcheron, M., Fischer, J.E., Reeves, S., Sharples, S.: Voice interfaces in everyday life. In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, pp. 1–12 (2018)

    Google Scholar 

Download references

Acknowledgments

The research supported by the youth foundation for humanities and social sciences of ministry of education of China, humanized design of intelligent mobile products for the elderly based on inclusive theory (20YJC760105).

Author information

Authors and Affiliations

  1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074, People’s Republic of China

    Lei Wu & Min Chen

Authors
  1. Lei Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Min Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lei Wu .

Editor information

Editors and Affiliations

  1. School of Industrial Engineering, Purdue University, West Lafayette, IN, USA

    Vincent G. Duffy

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Wu, L., Chen, M. (2022). A Bibliometric Analysis of Intelligent Voice Interaction Based on VOSviewer. In: Duffy, V.G. (eds) Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Health, Operations Management, and Design. HCII 2022. Lecture Notes in Computer Science, vol 13320. Springer, Cham. https://doi.org/10.1007/978-3-031-06018-2_31

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-06018-2_31

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06017-5

  • Online ISBN: 978-3-031-06018-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation