Skip to main content
SpringerLink
Log in

Voice Switching in Voice-Enabled Digital Assistants (VDAs)

  • Conference paper
  • First Online:
Human-Computer Interaction. Theory, Methods and Tools (HCII 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12762))

Included in the following conference series:

Abstract

Voice-enabled digital assistants (VDAs) provide users with options to switch the “out-of-the-box” or default voice interface. Numerous studies have investigated digital assistants. However, no studies have examined factors influencing user decisions to switch the default voice interface in VDAs. Informed by the similarity-attraction behavioral theory, we investigated whether perceived age, accent, gendered voice, and personality of the voice interface influence user decisions to switch the voice in VDAs. Guided by the status quo behavioral theory, we examined factors influencing user decisions to keep the default voice unchanged (status quo). We recruited thirty-one participants who took an online survey consisting of 42 questions, including 27 closed and 15 open-ended, collecting participants’ demographic information, experience in and knowledge of how to switch the voice, voice switching behavior, and preferences, among others. We employed the Big Five Personality Traits to assess the participants’ personality traits and the perceived personality of the voice in VDAs. We found that nearly 39% of the participants switched the voice interface in VDAs. Another finding is that the majority of male participants and all female participants (switchers and non-switchers) had a female-gendered voice in the VDAs. We detected a high correlation between the participants’ own personality traits and the perceived personality traits of their VDAs. Factors such as perceived age, accent, and gender did not influence the decision of the majority of the participants to switch the voice interface. The findings have implications for designing VDAs with personalities that leverage the user experience (UX).

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

Access this chapter

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 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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

Institutional subscriptions

References

  1. Juniper Research. https://www.juniperresearch.com/press/press-releases/number-of-voice-assistant-devices-in-use

  2. Atkinson, P., Barker, R.: ‘Hey alexa, what did i forget?’: networked devices, internet search and the delegation of human memory. Convergence 21(1), 52–65 (2020)

    Google Scholar 

  3. Ammari, T., Kaye, J., Tsai, J.Y., Bentley, F.: Music, search, and IoT: how people (really) use voice assistants. ACM Trans. Hum. Comput. Interact. 26(3), 1–28 (2019)

    Article  Google Scholar 

  4. Large, D.R., Clark, L., Quandt, A., Burnett, G., Skrypchuk, L.: Steering the conversation: a linguistic exploration of natural language interactions with a digital assistant during simulated driving. Appl. Ergon. 63, 53–61 (2017)

    Article  Google Scholar 

  5. Lee, K., Nass, C.: Designing social presence of social actors in human-computer interaction. In: Chi 2003: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 289–296. Association for Computing Machinery, New York (2003)

    Google Scholar 

  6. Nass, C., Brave, S.: Wired for Speech: How Voice Activates and Advances the Human-Computer Relationship. MIT Press, Cambridge, MA (2005)

    Google Scholar 

  7. Nass, C., Lee, K.M.: Does computer-synthesized speech manifest personality? Experimental tests of recognition, similarity-attraction, and consistency-attraction. J. Exp. Psychol. Appl. 7, 171–181 (2001)

    Article  Google Scholar 

  8. Aggarwal, P., McGill, A.L.: Is that car smiling at me? Schema congruity as a basis for evaluating anthropomorphized products. J. Consum. Res. 34(4), 468–479 (2007)

    Article  Google Scholar 

  9. Lee, E.-J., Nass, C., Brave, S.: Can computer-generated speech have gender? An experimental test of gender stereotype. In: Chi 2000: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 289–290. Association for Computing Machinery, New York (2000)

    Google Scholar 

  10. Nass, C., Moon, Y., Green, N.: Are computers gender-neutral? Gender stereotypic responses to computers. J. Appl. Soc. Psychol. 27(10), 864–876 (1997)

    Article  Google Scholar 

  11. Al-Natour, S., Benbasat, I., Cendetelli, R.T.: The role of design characteristics in shaping perceptions of similarity: the case of online shopping assistants. J. Assoc. Inf. Syst. 7(12), 821–861 (2006)

    Google Scholar 

  12. Perez Garcia, M., Saffon Lopez, S.: Building trust between users and telecommunications data driven virtual assistants. In: Iliadis, L., Maglogiannis, I., Plagianakos, V. (eds.) AIAI 2018. IAICT, vol. 519, pp. 628–637. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-92007-8_53

    Chapter  Google Scholar 

  13. Perez Garcia, M., Saffon Lopez, S., Donis, H.: Voice activated virtual assistants personality perceptions and desires: Comparing personality evaluation frameworks. In: HCI 2018: Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI), pp. 1–10. Association for Computing Machinery, New York (2018)

    Google Scholar 

  14. Lee, K.S., Kavya, P., Lasser, S.: Social interactions and relationships with an intelligent virtual agent. Int. J. Hum. Comput. Stud. 150, 102608 (2021)

    Google Scholar 

  15. Phan, T.: The materiality of the digital and the gendered voice of Siri. Transformations 29, 24–33 (2017)

    Google Scholar 

  16. Hwang, G., Lee. J., Oh, C.Y., Lee, J.: It sounds like a woman: exploring gender stereotypes in South Korean voice assistants. In: CHI EA 2019: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 1–6. Association for Computing Machinery, New York (2019)

    Google Scholar 

  17. Hoy, M.B.: Alexa, Siri, Cortana, and more: an introduction to voice assistants. Med. Ref. Serv. Q. 37(1), 81–88 (2018)

    Article  Google Scholar 

  18. Lopatovska, I., Rink, K., Knight, I.: Talk to me: exploring user interactions with the Amazon Alexa. J. Librariansh. Inf. Sci. 51(4), 984–987 (2019)

    Article  Google Scholar 

  19. Boyd, M., Wilson, N.: Just ask Siri? A pilot study comparing smartphone digital assistants and laptop Google searches for smoking cessation advice. PLoS ONE 13(3), 1–6 (2018)

    Article  Google Scholar 

  20. Qui, L., Benbasat, I.: The effects of text-to-speech voice and 3D avatars on consumer trust in the design of live help interface of electronic commerce. In: AMCIS 2004 Proceedings, pp. 3165–3173 (2004)

    Google Scholar 

  21. Qui, L., Benbasat, I.: Online consumer trust and live help interfaces: the effects of text-to-speech voice and three-dimensional avatars. Int. J. Hum. Comput. Interact. 19(1), 75–94 (2005)

    Article  Google Scholar 

  22. Qui, L., Benbasat, I.: Evaluating anthropomorphic product recommendation agents: a social relationship perspective to designing information systems. J. Manage. Inf. Syst. 25(4), 145–181 (2009)

    Article  Google Scholar 

  23. Qui, L., Benbasat, I.: A study of demographic embodiments of product recommendation agents in electronic commerce. Int. J. Hum Comput Stud. 68, 669–688 (2010)

    Article  Google Scholar 

  24. Elkins, A.C., Derrick, D.C.: The sound of trust: voice as a measurement of trust during integrations with embodied conversational agents. Group Decis. Negot. 22, 897–913 (2013)

    Article  Google Scholar 

  25. Evans, R.E., Kortum, P.: The impact of voice characteristics on user response in an interactive voice response system. Interact. Comput. 22(6), 606–614 (2010)

    Article  Google Scholar 

  26. Nunamaker, J.F., Derrick, D.C., Elkins, A.C., Burgoon, J.K., Patton, M.W.: Embodied conversational agent-based kiosk for automated interviewing. J. Manage. Inf. Syst. 28(1), 17–48 (2011)

    Google Scholar 

  27. Chattaraman, V., Kwon, W.-S., Gilbert, J.E., Ross, K.: Should AI-based, conversational digital assistants employ social- or task-oriented interaction style? A task-competency and reciprocity perspective for older adults. Comput. Hum. Behav. 90, 315–330 (2019)

    Article  Google Scholar 

  28. Samuelson, W., Zeckhauser, R.: Status quo bias in decision making. J. Risk Uncertain. 1, 7–59 (1988)

    Article  Google Scholar 

  29. Kahneman, D., Knetsch, J.L., Thaler, R.H.: Anomalies: the endowment effect, loss aversion, and status quo bias. J. Econ. Perspect. 5(1), 193–206 (1991)

    Article  Google Scholar 

  30. Cheng, K.G., Ernesto, F., Ovalle-Bahamón, R.E., Truong, K.N.: Barriers to acceptance of personal digital assistants for HIV/AIDS data collection in Angola. Int. J. Med. Informatics 80(8), 579–585 (2011)

    Article  Google Scholar 

  31. Kim, H.-W., Kankanhalli, A.: Investigating user resistance to information systems implementation: a status quo bias perspective. MIS Q. 33(3), 567–582 (2009)

    Article  Google Scholar 

  32. Kahneman, D., Tversky, A.: Choices, values, and frames. Am. Psychol. 39(4), 341–350 (1984)

    Article  Google Scholar 

  33. Tversky, A., Kahneman, D.: Rational choice and the framing of decisions. J. Bus. 59(4), 251–278 (1986)

    Article  Google Scholar 

  34. Gal, D., Rucker, D.D.: The loss of loss aversion: will it loom larger than its gain? J. Consum. Psychol. 28(3), 497–516 (2018)

    Article  Google Scholar 

  35. Ritov, I., Baron, J.: Status-quo and omission bias. J. Risk Uncertain. 5, 49–61 (1992)

    Article  Google Scholar 

  36. Interaction Design Foundation. https://www.interaction-design.org/literature/article/hick-s-law-making-the-choice-easier-for-users

  37. Berscheid, E., Dion, K., Walster, W., Walster, G.W.: Physical attractiveness and dating choice: a test of the matching hypothesis. J. Exp. Soc. Psychol. 7, 173–189 (1971)

    Article  Google Scholar 

  38. Byrne, D.: The Attraction Paradigm. Academic Press, New York (1971)

    Google Scholar 

  39. Ramadhar, S., Ho, S.Y.: Attitudes and attraction: a new test of the attraction, repulsion and similarity-dissimilarity asymmetry hypotheses. Br. J. Soc. Psychol. 39(2), 197–211 (2000)

    Article  Google Scholar 

  40. Rosenbaum, M.E.: The repulsion hypothesis: on the nondevelopment of relationships. J. Pers. Soc. Psychol. 51(6), 1156–1166 (1986)

    Article  Google Scholar 

  41. Blankenship, V., Hnat, T.G., Hess, T.G., Brown, D.R.: Similarity of personality attributes. J. Soc. Pers. Relat. 1(4), 415–432 (1984)

    Article  Google Scholar 

  42. Montano, K.J., Tigue, C.C., Isenstein, S.G.E., Barclay, P., Fienberg, D.R.: Men’s voice pitch influences women’s trusting behavior. Evol. Hum. Behav. 38, 293–297 (2017)

    Article  Google Scholar 

  43. Borkowska, B., Pawlowski, B.: Female voice frequency in the context of dominance and attractiveness perception. Anim. Behav. 82, 55–59 (2011)

    Article  Google Scholar 

  44. Aylett, M.P., Vinciarelli, A., Wester, M.: Speech synthesis for the generation of artificial personality. IEEE Trans. Affect. Comput. 11(2), 361–372 (2020)

    Article  Google Scholar 

  45. McCrae, R.R., Costa, P.T.: Validation of the five-factor model of personality across instruments and observers. J. Pers. Soc. Psychol. 52(1), 81–90 (1987)

    Google Scholar 

  46. Mount, M.K., Barrick, M.R., Strauss, J.P.: Validity of observer ratings of the Big Five personality factors. J. Appl. Psychol. 79(2), 272–280 (1994)

    Article  Google Scholar 

  47. Gurven, M., von Rueden, C., Massenkoff, M., Kaplan, H., Vie, M.L.: How universal is the Big Five? Testing the five-factor model of personality variation among forager-farmers in the Bolivian Amazon. J. Pers. Soc. Psychol. 104(2), 354–370 (2013)

    Article  Google Scholar 

  48. Gosling, S.D., Rentfrow, P.J., Swann Jr., W.B.: A very brief measure of the Big-Five personality domains. J. Res. Pers. 37(6), 504–528 (2003)

    Article  Google Scholar 

  49. Fusion Hill. https://www.fusionhill.com/hey-siri-whered-you-get-your-personality-four-ways-to-make-a-digital-assistant-engaging

Download references

Author information

Authors and Affiliations

  1. University of Tennessee, Knoxville, TN, 37996, USA

    Dania Bilal & Jessica K. Barfield

Authors
  1. Dania Bilal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jessica K. Barfield
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dania Bilal .

Editor information

Editors and Affiliations

  1. The Open University of Japan, Chiba, Japan

    Masaaki Kurosu

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bilal, D., Barfield, J.K. (2021). Voice Switching in Voice-Enabled Digital Assistants (VDAs). In: Kurosu, M. (eds) Human-Computer Interaction. Theory, Methods and Tools. HCII 2021. Lecture Notes in Computer Science(), vol 12762. Springer, Cham. https://doi.org/10.1007/978-3-030-78462-1_39

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-78462-1_39

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78461-4

  • Online ISBN: 978-3-030-78462-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation