Non-Humanoid Robotics Speech Synthesizer: Design and User Perception

Abstract

This paper introduces a Non-Humanoid Robotics Speech Synthesizer (NRSS) designed for identifying and greeting individuals through verbal responses. The system integrates a text-tospeech module, ultrasonic sensor, control circuitry, and a microcontroller, all programmed using Arduino. This setup enables efficient person identification, greetings, and information relay. Building on previous studies about robot speech perception, this study explores user reactions to the NRSS during initial encounters. The premise is that non-humanoid robots with verbal capabilities can be positively perceived by users. To test this, 54 participants of various ages and robotic experiences evaluated the NRSS. Using one-way ANOVA, the study found that the NRSS was positively perceived in terms of competence and comfort across demographics, although perceptions of warmth varied. The study concludes that the NRSS excels in environments where perceived competence and user comfort are paramount, such as public greeting or guidance roles, due to its low cost and ease of construction, though its utility can extend to various other domains. 

Keywords

• Non-humanoid robot
• Robotic experience
• Competence
• Warmth
• Discomfort

References

1. Ling, H., Shen, Y., Zhang, Z., Zheng, S., and Zhang, D., “Structure design and analysis of a new greeting robot”, IOSR Journal of Mechanical and Civil Engineering, 14(1): 34–39, (2017). DOI: https://doi.org/10.9790/1684-1401063439
2. Barua, R., Bhowmik, S., Dey, A., and Mondal, J., “Advances of the robotics technology in modern minimally invasive surgery”, in Design and Control Advances in Robotics, IGI Global, 91–104, (2023). DOI: https://doi.org/10.4018/978-1-6684-5381-0.ch006
3. Siripurapu, S., Darimireddy, N. K., Chehri, A., and AV, P., “Technological advancements and elucidation gadgets for healthcare applications: an exhaustive methodological review-part-II (robotics, drones, 3D-printing, internet of things, virtual/augmented and mixed reality)”, Electronics, 12(3): 548, (2023). DOI: https://doi.org/10.3390/electronics12030548
4. Fraune, M. R., Oisted, B. C., Sembrowski, C. E., Gates, K. A., Krupp, M. M., and Šabanović, S., “Effects of robot-human versus robot-robot behavior and entitativity on anthropomorphism and willingness to interact”, Computers in Human Behavior, 105: 106220, (2020). DOI: https://doi.org/10.1016/j.chb.2019.106220
5. Barlas, Z., “When robots tell you what to do: sense of agency in human-and robot-guided actions”, Consciousness and Cognition, 75: 102819, (2019). DOI: https://doi.org/10.1016/j.concog.2019.102819
6. Goffman, E., “Behavior in Public Places”, New York: Free Press, (1963).
7. Goffman, E., “Encounters”, Indianapolis: Bobbs-Merrill, (1961).
8. Schiffrin, D., “Opening encounters”, American Sociological Review, 42(5): 679–691, (1977). DOI: https://doi.org/10.2307/2094861

9. De Wit, J., Vogt, P., and Krahmer, E., “The design and observed effects of robot-performed manual gestures: a systematic review”, ACM Transactions on Human-Robot Interaction, 12(1): 1–62, (2023). DOI: https://doi.org/10.1145/3565473
10. Linnunsalo, S., Küster, D., Yrttiaho, S., Peltola, M. J., and Hietanen, J. K., “Psychophysiological responses to eye contact with a humanoid robot: impact of perceived intentionality”, Neuropsychologia, 189: 108668, (2023). DOI: https://doi.org/10.1016/j.neuropsychologia.2023.108668
11. Yan, Z., Song, Y., Zhou, R., Wang, L., Wang, Z., and Dai, Z., “Facial expression realization of humanoid robot head and strain-based anthropomorphic evaluation of robot facial expressions”, Biomimetics, 9(3): 122, (2024). DOI: https://doi.org/10.3390/biomimetics9030122
12. [12] Minh, T. N., and Truong, T. N., “A comprehensive review: interaction of appearance and behavior, artificial skin, and humanoid robot”, Journal of Robotics, 2023(1): 5589845, (2023). DOI: https://doi.org/10.1155/2023/5589845
13. Goetz, J., Kiesler, S., and Powers, A., “Matching robot appearance and behavior to tasks to improve human-robot cooperation”, in Proceedings of the 12th IEEE International Workshop on Robot and Human Interactive Communication (RO-MAN 2003), IEEE, 55–60, (2003). DOI: https://doi.org/10.1109/ROMAN.2003.1251796
14. Munteanu-Calen, A., “Reactions to and interactions with a non-verbal robot: a case study on people’s interpretation of and perception of interacting with a non-humanoid and non-verbal robot”, Diploma Thesis, Technische Universität Wien, reposiTUm, (2023). DOI: https://doi.org/10.34726/hss.2023.107249
15. Anderson-Bashan, L., Megidish, B., Erel, H., Wald, I., Hoffman, G., Zuckerman, O., and Grishko, A., “The greeting machine: an abstract robotic object for opening encounters”, in 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), IEEE, 595–602, (2018). DOI: https://doi.org/10.1109/ROMAN.2018.8525806
16. Parlitz, C., Hägele, M., Klein, P., Seifert, J., and Dautenhahn, K., “Care-o-bot 3-rationale for human-robot interaction design”, in Proceedings of the 39th International Symposium on Robotics (ISR), Seoul, Korea, 275–280, (2008).
17. Hoffman, G., and Ju, W., “Designing robots with movement in mind”, Journal of Human-Robot Interaction, 3(1): 91–122, (2014). DOI: https://doi.org/10.5898/JHRI.3.1.Hoffman
18. Yang, C., Wu, X., Lin, M., Lin, R., and Wu, D., “A review of advances in underwater humanoid robots for human-machine cooperation”, Robotics and Autonomous Systems, 180: 104744, (2024). DOI: https://doi.org/10.1016/j.robot.2024.104744
19. Luo, J., Domova, V., and Kim, L. H., “Impact of multi-robot presence and anthropomorphism on human cognition and emotion”, in Proceedings of the CHI Conference on Human Factors in Computing Systems, 1–15, (2024). DOI: https://doi.org/10.1145/3613904.3642516
20. Stroessner, S. J., and Benitez, J., “The social perception of humanoid and non-humanoid robots: effects of gendered and machinelike features”, International Journal of Social Robotics, 11: 305–315, (2019). DOI: https://doi.org/10.1007/s12369-018-0502-7
21. Cowen, A. S., Elfenbein, H. A., Laukka, P., and Keltner, D., “Mapping 24 emotions conveyed by brief human vocalization”, American Psychologist, 74(6): 698–712, (2019). DOI: https://doi.org/10.1037/amp0000399
22. Liu, J., and Chiang, H. D., “Maximizing available delivery capability of unbalanced distribution networks for high penetration of distributed generators”, IEEE Transactions on Power Delivery, 32(3): 1196–1202, (2017). DOI: https://doi.org/10.1109/TPWRD.2016.2593985
23. Goffman, E., “Relations in Public”, Transaction Publishers, (2009).
24. Bainbridge, W. A., Hart, J., Kim, E. S., and Scassellati, B., “The effect of presence on human-robot interaction”, in RO-MAN 2008: The 17th IEEE International Symposium on Robot and Human Interactive Communication, IEEE, 701–706, (2008). DOI: https://doi.org/10.1109/ROMAN.2008.4600721
25. Bretan, M., Hoffman, G., and Weinberg, G., “Emotionally expressive dynamic physical behaviors in robots”, International Journal of Human-Computer Studies, 78: 1–16, (2015). DOI: https://doi.org/10.1016/j.ijhcs.2015.02.002
26. Marin, V. A., Cominelli, L., Dell’Orletta, F., and Scilingo, E. P., “Verbal communication in robotics: a study on salient terms, research fields and trends in the last decades based on a computational linguistic analysis”, Frontiers in Computer Science, 2: 591164, (2021). DOI: https://doi.org/10.3389/fcomp.2020.591164
27. Budiharto, W., Cahyani, A. D., Rumondor, P. C. B., and Suhartono, D., “EduRobot: intelligent humanoid robot with natural interaction for education and entertainment”, Procedia Computer Science, 116: 564–570, (2017). DOI: https://doi.org/10.1016/j.procs.2017.10.046
28. Zinchenko, K., Komarov, O., and Song, K. T., “Virtual reality control of a robotic camera holder for minimally invasive surgery”, in 2017 11th Asian Control Conference (ASCC), IEEE, 970–975, (2017). DOI: https://doi.org/10.1109/ASCC.2017.8287228
29. Zhou, B., Wu, K., Lv, P., Wang, J., Chen, G., Ji, B., and Liu, S., “A new remote health-care system based on moving robot intended for the elderly at home”, Journal of Healthcare Engineering, 2018(1): 4949863, (2018). DOI: https://doi.org/10.1155/2018/4949863
30. Schulz, R., Talbot, B., Lam, O., Dayoub, F., Corke, P., Upcroft, B., and Wyeth, G., “Robot navigation using human cues: a robot navigation system for symbolic goal-directed exploration”, in 2015 IEEE International Conference on Robotics and Automation (ICRA), IEEE, 1100–1105, (2015). DOI: https://doi.org/10.1109/ICRA.2015.7139338
31. Romero-Lankao, P., Wilson, A., Sperling, J., Miller, C., Zimny-Schmitt, D., Sovacool, B., and Gearhart, C., “Of actors, cities and energy systems: advancing the transformative potential of urban electrification”, Progress in Energy, 3(3), (2021). DOI: https://doi.org/10.1088/2516-1083/ac0a73
32. Birk, A., “Behavior-based robotics, its scope and its prospects”, in IECON'98: Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society, IEEE, 2180–2185, (1998). DOI: https://doi.org/10.1109/IECON.1998.724034
33. Carpinella, C. M., Wyman, A. B., Perez, M. A., and Stroessner, S. J., “The robotic social attributes scale (ROSAS): development and validation”, in Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, 254–262, (2017). DOI: https://doi.org/10.1145/2909824.3020208
34. Bartneck, C., Kulić, D., Croft, E., and Zoghbi, S., “Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots”, International Journal of Social Robotics, 1: 71–81, (2009). DOI: https://doi.org/10.1007/s12369-008-0001-3
35. Ramachandran, K. M., and Tsokos, C. P., “Mathematical Statistics with Applications in R”, Academic Press, (2020).
36. Larson, M. G., “Analysis of variance”, Circulation, 117(1): 115–121, (2008). DOI: https://doi.org/10.1161/CIRCULATIONAHA.107.654335