AccScience Publishing / DP / Online First / DOI: 10.36922/DP025370040
ARTICLE

Children’s preferences for virtual agents with natural and synthetic voices: Exploring developmental differences in willingness to interact and perceived voice quality

Miriam Veneziano1* Maria Sarno1 Maria Santina Ler1 Marialucia Cuciniello1 Terry Amorese1 Attilio Trusio2 Olga Gordeeva3 Gennaro Cordasco4 Anna Esposito1,5,6*
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1 Department of Psychology, Faculty of Psychology 2, University of Campania “Luigi Vanvitelli,” Caserta, Caserta, Campania, Italy
2 State Education Department III Carlo Collodi District, Pagani, Salerno, Italy
3 Acapela Group SA, Mons, Hainaut, Belgium
4 Department of Computer Science, Faculty of Computer Science, University of Salerno, Fisciano, Salerno, Italy
5 Italian Society for Neural Networks, Vietri Sul Mare, Salerno, Italy
6 Corvinus Institute for Advanced Studies, Corvinus University of Budapest, Budapest, Hungary
Received: 12 September 2025 | Revised: 24 October 2025 | Accepted: 19 January 2026 | Published online: 27 March 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract

Investigations into children’s perception and acceptance of new technologies, including voice chatbots, robots, and virtual agents, represent an emerging and rapidly expanding field of academic research. These interactive dialogue systems offer new opportunities in various settings (e.g., educational, therapeutic, and health settings) by providing innovative tools to improve the effectiveness of interactions and overall well-being. This study investigates children’s preferences for eight virtual agents: four with natural human voices (one adult male, one adult female, one boy, and one girl) and four with synthetic voices matching the same age and gender distribution. A sample of 132 children aged between 4 and 10 years (excluding 6-year-olds) was divided into four age groups to assess whether preferences change with development. Results suggest that younger children showed no clear preference between natural and synthetic voices in terms of interaction. In contrast, older children displayed a stronger preference for natural voices, likely due to their engaging qualities. While no significant differences in voice quality were noted among younger children, older children favored natural adult voices, which they perceived as clearer and more trustworthy.

Keywords
Children
Virtual agents
Acceptance
Synthetic and natural voice
Funding
This research was funded by the EU Horizon 2020 program (grant no.: 101182965 [CRYSTAL]), the NextGenerationEU PNRR Mission 4 Component 2 Investment 1.1 (D.D 1409 del 14-09-2022), the PRIN 2022 under the IRRESPECTIVE project (Code P20222MYKE; CUP: B53D23025980001), and the PNRR–MUR under AI-PATTERNS FAIR Project (CUP: E63C22002150007).
Conflict of interest
The authors declare they have no competing interests.
References
  1. Rakison DH, Poulin-Dubois D. Developmental origin of the animate–inanimate distinction. Psychol Bull. 2001;127(2):209-228. doi: 10.1037/0033-2909.127.2.209

 

  1. Opfer JE, Gelman SA. Development of the animate-inanimate distinction. In: Zelazo PD, editor. The Wiley-Blackwell Handbook of Childhood Cognitive Development. 2nd ed. Hoboken, NJ, USA: Wiley-Blackwell; 2011:213-238. doi: 10.1002/9781444325485.ch8

 

  1. Caramazza A, Shelton JR. Domain-specific knowledge systems in the brain: The animate-inanimate distinction. J Cogn Neurosci. 1998;10(1):1-34. doi: 10.1162/089892998563752

 

  1. Tanaka F, Cicourel A, Movellan JR. Socialization between toddlers and robots at an early childhood education center. Proc Natl Acad Sci USA. 2007;104(46):17954-17958. doi: 10.1073/pnas.0707769104

 

  1. Melson GF, Kahn PH Jr, Beck A, et al. Children’s behavior toward and understanding of robotic and living dogs. J Appl Dev Psychol. 2009;30(2):92-102. doi: 10.1016/j.appdev.2008.10.011

 

  1. Kory-Westlund JM, Breazeal C. Exploring the effects of a social robot’s speech entrainment and backstory on young children’s emotion, rapport, relationship, and learning. Front Robot AI. 2019;6:54. doi: 10.3389/frobt.2019.00054

 

  1. Roesler E. Anthropomorphic framing and failure comprehensibility influence different facets of trust towards industrial robots. Front Robot AI. 2023;10:1235017. doi: 10.3389/frobt.2023.1235017

 

  1. Festerling J, Siraj I. Anthropomorphizing technology: A conceptual review of anthropomorphism research and how it relates to children’s engagements with digital voice assistants. Integr Psychol Behav Sci. 2022;56(3):709-738. doi: 10.1007/s12124-021-09668-y

 

  1. Kahn PH Jr, Kanda T, Ishiguro H, et al. “Robovie, you’ll have to go into the closet now”: Children’s social and moral relationships with a humanoid robot. Dev Psychol. 2012;48(2):303-314. doi: 10.1037/a0027033

 

  1. van Duuren M, Scaife M. Because a robot’s brain hasn’t got a brain, it just controls itself—Children’s attributions of brain-related behaviour to intelligent artefacts. Eur J Psychol Educ. 1996;11:365-376. doi: 10.1007/BF03173278

 

  1. Mikropoulos TA, Misailidi P, Bonoti F. Attributing human properties to computer artifacts: Developmental changes in children’s understanding of the animate-inanimate distinction. Psychol J Hell Psychol Soc. 2003;10(2):123-140. doi: 10.12681/psy_hps.23951

 

  1. Lee S, Kim S, Lee S. What does your agent look like? A drawing study to understand users’ perceived persona of conversational agent. In: Proceedings of the Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems. ACM; 2019:1-6. doi: 10.1145/3290607.3312796

 

  1. Kory-Westlund JM. Implications of children’s social, emotional, and relational interactions with robots for human–robot empathy. In: Smith M, Jones L, editors. Conversations on Empathy: Interdisciplinary Perspectives on Empathy, Imagination and Othering. London, UK: Routledge; 2023:256-278. doi: 10.4324/9781003189978-17

 

  1. Xu Y, Warschauer M. What are you talking to? Understanding children’s perceptions of conversational agents. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. ACM; 2020:1-13. doi: 10.1145/3313831.3376416

 

  1. Wellman HM, Cross D, Watson J. Meta-analysis of theory-of-mind development: The truth about false belief. Child Dev. 2001;72(3):655-684. doi: 10.1111/1467-8624.00304

 

  1. Banks J. Theory of mind in social robots: Replication of five established human tests. Int J Soc Robot. 2020;12(2):403-414. doi: 10.1007/s12369-019-00588-x

 

  1. Mao Y, Liu S, Ni Q, Lin X, He L. A review on machine theory of mind. IEEE Trans Comput Soc Syst. 2024;11(6):7114-7132. doi: 10.1109/TCSS.2024.3416707

 

  1. Mou W, Ruocco M, Zanatto D, Cangelosi A. When would you trust a robot? A study on trust and theory of mind in human-robot interactions. In: Proceedings of the 2020 IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). IEEE; 2020:956-962. doi: 10.1109/RO-MAN47096.2020.9223551

 

  1. Xu Y, Aubele J, Vigil V, et al. Dialogue with a conversational agent promotes children’s story comprehension via enhancing engagement. Child Dev. 2022;93(2):e149-e167. doi: 10.1111/cdev.13708

 

  1. Hiniker A, Wang A, Tran J, et al. Can conversational agents change the way children talk to people? In: Proceedings of the 20th Annual ACM Interaction Design and Children Conference. ACM; 2021: 338-349. doi: 10.1145/3459990.3460695

 

  1. Catania F, Spitale M, Garzotto F. Conversational agents in therapeutic interventions for neurodevelopmental disorders: A survey. ACM Comput Surv. 2023;55(10):1-34. doi: 10.1145/3564269

 

  1. Veneziano M, Cuciniello M, Amorese T, et al. How willingness to interact and intelligibility of the voice affect children’s interaction with an interactive dialogue system: A pilot study. In: Proceedings of the 2024 IEEE International Conference on Cognitive Infocommunications. IEEE; 2024:173-180. doi: 10.1109/CogInfoCom63007.2024.10894720

 

  1. Esposito A, Amorese T, Cuciniello M, et al. Elder user’s attitude toward assistive virtual agents: The role of voice and gender. J Ambient Intell Humaniz Comput. 2021;12(4):4429-4436. doi: 10.1007/s12652-019-01423-x

 

  1. Kory-Westlund JM, Breazeal C. Assessing children’s perceptions and acceptance of a social robot. In: Proceedings of the 18th ACM International Conference on Interaction Design and Children. ACM; 2019:38-50. doi: 10.1145/3311927.3323143

 

  1. Barrouillet P. Theories of cognitive development: From Piaget to today. Dev Rev. 2015;38:1-12. doi: 10.1016/j.dr.2015.07.004

 

  1. Severson RL, Carlson SM. Behaving as or behaving as if? Children’s conceptions of personified robots and the emergence of a new ontological category. Neural Netw. 2010;23(8-9):1099-1103. doi: 10.1016/j.neunet.2010.08.014

 

  1. Druga S, Williams R, Breazeal C, Resnick M. Hey Google, is it OK if I eat you? Initial explorations in child-agent interaction. In: Proceedings of the 2017 Conference on Interaction Design and Children. ACM; 2017:595-600. doi: 10.1145/3078072.3084330
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