Abstract
Voice Assistants (VAs) are growing in popularity, but some barriers to these systems’ usage and adoption still prevail. Such obstacles may be related to users’ mental models, which are unaligned with VAs’ actual capabilities. Considering the influence of design aspects on users’ perceptions, VA designers have a significant role in designing solutions that improve users’ mental models and the quality of interactions. Thus, this study aimed to explore the opinions of professionals experienced in conversational design concerning users’ mental models of VAs. Specifically, we aimed to identify the experts’ opinions on 1) causes for users’ misperceptions of VAs and 2) potential solutions to deal with the issue. To this end, we conducted a three-round questionnaire-based Delphi study with developers and researchers of conversational interfaces. The results showed that design aspects such as VAs’ high humanness and the lack of transparency influence users’ mental models. Nevertheless, removing VAs’ humanness and excessively displaying information about VAs might not be an immediate solution. In turn, designers should assess the context and task domains in which the VA will be used to guide design decisions. Finally, developing teams should have a correct and homogeneous understanding of VAs and possess the necessary knowledge, skills, and tools to employ solutions properly.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
West, M., Kraut, R., Han Ei, C.: I’d blush if I could (2019). https://unesdoc.unesco.org/ark:/48223/pf0000367416.page=1. Accessed 29 Apr 2019
Statista. Total number of Amazon Alexa skills in selected countries as of January 2020 (2020). https://www.statista.com/statistics/917900/selected-countries-amazon-alexa-skill-count/. Accessed 2 Nov 2021
Vailshery, L.S.: Number of digital voice assistants in use worldwide from 2019 to 2024 (in billions) (2021). https://www.statista.com/statistics/973815/worldwide-digital-voice-assistant-in-use/. Accessed 2 Jan 2022
Vailshery, L.S.: Voice technology - Statistics & Facts (2022). https://www.statista.com/topics/6760/voice-technology/#dossierKeyfigures. Accessed 2 Jan 2022
Robart, A.: Looking Ahead to the Voice Era (2017). https://www.comscore.com/Insights/Presentations-and-Whitepapers/2017/Looking-Ahead-to-the-Voice-Era. Accessed 29 Apr 2019
McLean, G., Osei-Frimpong, K.: Hey Alexa … examine the variables influencing the use of artificial intelligent in-home voice assistants. Comput. Human Behav. 99, 28–37 (2019). https://doi.org/10.1016/j.chb.2019.05.009
White-Smith, H., Cunha, S., Koray, E., Keating, P.: Technology Tracker - Q1 2019 (2019). https://www.ipsos.com/sites/default/files/ct/publication/documents/2019-03/techtracker_report_q12019_final_1.pdf. Accessed 29 Apr 2019
Maués, M.P.: Marcela Pedroso Maués Um olhar sobre os assistentes virtuais personificados e a voz como interface. Pontifical Catholic University of Rio de Janeiro (2019)
Purington, A., Taft, J.G., Sannon, S., et al.: “Alexa is my new BFF”: Social roles, user satisfaction, and personification of the Amazon Echo. Conf. Hum. Factors Comput. Syst. – Proc. Part F 1276, 2853–2859 (2017). https://doi.org/10.1145/3027063.3053246
Beneteau, E., Richards, O.K., Zhang, M., et al.: Communication breakdowns between families and Alexa. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 1–13. Association for Computing Machinery, New York (2019)
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. ACM, New York (2018)
Moriuchi, E.: Okay, Google!: An empirical study on voice assistants on consumer engagement and loyalty. Psychol. Mark. 36, 489–501 (2019). https://doi.org/10.1002/mar.21192
Burbach, L., Halbach, P., Plettenberg, N., et al.: “Hey, Siri”, “Ok, Google”, “Alexa”. Acceptance-relevant factors of virtual voice-assistants. In: 2019 IEEE International Professional Communication Conference (ProComm), pp. 101–111. IEEE (2019)
Norman, D.: The Design of Everyday Things, Revised an. Basic books, New York (2013)
Moreno, A., Mossio, M.: Cognition. In: Biological Autonomy. HPTLS, vol. 12, pp. 167–193. Springer, Dordrecht (2015). https://doi.org/10.1007/978-94-017-9837-2_7
Wilson, J.R., Rutherford, A.: Mental models: theory and application in human factors. Hum. Factors 31, 617–634 (1989). https://doi.org/10.1177/001872088903100601
Cho, M., Lee, S., Lee, K.-P.: Once a kind friend is now a thing. In: Proceedings of the 2019 on Designing Interactive Systems Conference, pp. 1557–1569. ACM, New York (2019)
Luger, E., Sellen, A.: “Like Having a Really Bad PA”: the gulf between user expectation and experience of conversational agents. In: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, pp. 5286–5297. Association for Computing Machinery, New York (2016)
Motta, I., Quaresma, M.: Understanding task differences to leverage the usability and adoption of voice assistants (VAs). In: Soares, M.M., Rosenzweig, E., Marcus, A. (eds.) HCII 2021. LNCS, vol. 12781, pp. 483–502. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-78227-6_35
Myers, C., Furqan, A., Nebolsky, J., et al.: Patterns for how users overcome obstacles in voice user interfaces, pp. 1–7. In: Conference on Human Factors in Computing Systems - Proceedings (2018)
Motta, I., Quaresma, M.: Users’ error recovery strategies in the interaction with voice assistants (VAs). In: Black, N.L., Neumann, W.P., Noy, I. (eds.) IEA 2021. LNNS, vol. 223, pp. 658–666. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-74614-8_82
Kim, J., Jeong, M., Lee, S.C.: “Why did this voice agent not understand me?” In: Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications: Adjunct Proceedings, pp. 146–150. ACM, New York (2019)
Ammari, T., Kaye, J., Tsai, J.Y., Bentley, F.: Music, search, and IoT: how people (really) use voice assistants. ACM Trans. Comput. Interact. (2019). https://doi.org/10.1145/3311956
Cowan, B.R., Pantidi, N., Coyle, D., et al.: “What can i help you with?” In: Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services, pp. 1–12. ACM, New York (2017)
Javed, Y., Sethi, S., Jadoun, A.: Alexa’s voice recording behavior. In: Proceedings of the 14th International Conference on Availability, Reliability and Security, pp. 1–10. ACM, New York (2019)
Fish, L.S., Busby, D.M.: The Delphi method. In: Sprenkle, D.H., Piercy, F.P. (eds.) Research Methods in Family Therapy, 2nd edn, pp. 238–253. Guilford Publications (2005)
Linstone, H., Turrof, M.: The Delphi Method: Techniques and Applications. Addison-Wesley (1975)
Delbecq, A.L., Van de Ven, A.H., Gustafson, D.H.: Group Techniques for Program Planning: A Guide to Nominal Group and Delphi Processes. Scott, Foresman and Company, Glenview (1975)
Barnum, C.: Usability Testing Essentials. Ready, Set... Elsevier, Burlington (2011)
Giannarou, L., Zervas, E.: Using Delphi technique to build consensus in practice. Int. J. Bus. Sci. Appl. Manag. 9, 65–82 (2014)
Balasuriya, S.S., Sitbon, L., Bayor, A.A., et al.: Use of voice activated interfaces by people with intellectual disability. In: Proceedings of the 30th Australian Conference on Computer-Human Interaction, pp. 102–112. ACM, New York (2018)
Garg, R., Sengupta, S.: He is just like me. Proc. ACM Interact. Mobile Wearab. Ubiquit. Technol. 4, 1–24 (2020). https://doi.org/10.1145/3381002
Kirschthaler, P., Porcheron, M., Fischer, J.E.: What can i say?: Effects of discoverability in VUIs on task performance and user experience. In: ACM International Conference Proceeding Series (2020)
Hackos, J.T., Redish, J.: User and Task Analysis for Interface Design. Wiley, Toronto (1998)
Chen, M.-L., Wang, H.-C.: How personal experience and technical knowledge affect using conversational agents. In: Proceedings of the 23rd International Conference on Intelligent User Interfaces Companion, pp. 1–2. ACM, New York (2018)
Souza, B., Quaresma, M.: O perfil do UX designer: um panorama da visão do mercado de trabalho. In: Blucher Design Proceedings, p. 6121. Editora Blucher, São Paulo (2019). https://doi.org/10.5151/ped2018-7.1_AIC_03
Da Costa Brito, L., Quaresma, M.M.R.: O design centrado no usuário nas metodologias ágeis. In: Blucher Design Proceedings, pp. 125–139. Editora Blucher, São Paulo (2019)
Zwakman, D.S., Pal, D., Arpnikanondt, C.: Usability evaluation of artificial intelligence-based voice assistants: the case of Amazon Alexa. SN Comput. Sci. 2(1), 1–16 (2021). https://doi.org/10.1007/s42979-020-00424-4
Moraes, A.: Algumas estratégias para a implementação da pesquisa em design considerando sua importância para a consolidação do ensino de design. Número Especial, Estud em Des Maio (1997)
Acknowledgements
This study was financed in part by FAPERJ and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Motta, I., Quaresma, M. (2022). Exploring the Opinions of Experts in Conversational Design: A Study on Users’ Mental Models of Voice Assistants. In: Kurosu, M. (eds) Human-Computer Interaction. User Experience and Behavior. HCII 2022. Lecture Notes in Computer Science, vol 13304. Springer, Cham. https://doi.org/10.1007/978-3-031-05412-9_34
Download citation
DOI: https://doi.org/10.1007/978-3-031-05412-9_34
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-05411-2
Online ISBN: 978-3-031-05412-9
eBook Packages: Computer ScienceComputer Science (R0)