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International Journal of Social Robotics

Published in:

22-05-2020

Effects of Different Types of Social Robot Voices on Affective Evaluations in Different Application Fields

Authors: Xiao Dou, Chih-Fu Wu, Kai-Chieh Lin, Senzhong Gan, Tzu-Min Tseng

Published in: International Journal of Social Robotics | Issue 4/2021

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Abstract

As the roles of social robots are increasingly diverse, it is important to design the robots according to their application fields and end-users needs. A robot’s voice is a strong social cue, the design of which can influence people’s affective evaluation and acceptance toward robots. The aim of this study is to investigate the affective evaluation of different robot voices in various application fields, and obtained suitable voice types for robots in different application fields. In particular, this study focused on the three applications (i.e., shopping reception, home companion, and education), investigated the effect of voice types (i.e., male, female, child, and synthetic) of social robots on the affective evaluation of users. Principal component analysis identified three latent influencing factors (i.e., social skills, competence and the state of the interaction relationships). Multivariable analysis proved that for overall acceptance, significant interaction effects existed between robots’ voice types and their application fields. For shopping reception robots, the most acceptable voice type is adult male voice and child voice. For home companion robots, the most acceptable robot voice types are adult male and child voices. For education robots, the most acceptable voice types are adult female and male voices. The results of this study are expected to construct design principles for robot voice design in various applications.

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Ejdys J, Halicka K (2018) Sustainable adaptation of new technology—the case of humanoids used for the care of older adults. Sustainability 10(10):3770CrossRef

Oh K, Kim M (2010) Social attributes of robotic products: observations of child–robot interactions in a school environment. Int J Des 4:45–55

Looije R, Neerincx MA, Cnossen F (2010) Persuasive robotic assistant for health self-management of older adults: design and evaluation of social behaviors. Int J Hum Comput Stud 68:386–397. https://doi.org/10.1016/j.ijhcs.2009.08.007CrossRef

Louie WYG, McColl D, Nejat G (2014) Acceptance and attitudes toward a human-like socially assistive robot by older adults. Assist Technol 26(3):140–150. https://doi.org/10.1080/10400435.2013.869703CrossRef

Chang RCS, Lu HP, Yang P (2018) Stereotypes or golden rules? Exploring likable voice traits of social robots as active aging companions for tech-savvy baby boomers in Taiwan. Comput Hum Behav 84:194–210. https://doi.org/10.1016/j.chb.2018.02.025CrossRef

Takayama L, Ju W, Nass C (2008) Beyond dirty, dangerous and dull: what everyday people think robots should do. In: 3rd ACM/IEEE international conference on human–robot interaction (HRI), Amsterdam, Netherlands, March 12–15 2008. IEEE, pp 25–32

Berry DS (1992) Vocal types and stereotypes: joint effects of vocal attractiveness and vocal maturity on person perception. J Nonverbal Behav 16(1):41–54. https://doi.org/10.1007/BF00986878CrossRef

IFR-International Federation of Robotics (2012) Introduction into service robots, Technical report, p 4

Dautenhahn K (2007) Methodology & themes of human–robot interaction: a growing research field. Int J Adv Robot Syst 4(1):15CrossRef

10.

De Graaf MM, Allouch SB, Klamer T (2015) Sharing a life with Harvey: exploring the acceptance of and relationship-building with a social robot. Comput Hum Behav 43:1–14. https://doi.org/10.1016/j.chb.2014.10.030CrossRef

11.

Cheng YW, Sun PC, Chen NS (2018) The essential applications of educational robot: requirement analysis from the perspectives of experts, researchers and instructors. Comput Educ 126:399–416. https://doi.org/10.1016/j.compedu.2018.07.020CrossRef

12.

Broadbent E, Feerst DA, Lee SH, Robinson H, Albo-Canals J, Ahn HS, MacDonald BA (2018) How could companion robots be useful in rural schools? Int J Soc Robot 10(3):295–307CrossRef

13.

Tay B, Jung Y, Park T (2014) When stereotypes meet robots: the double-edge sword of robot gender and personality in human–robot interaction. Comput Hum Behav 38:75–84CrossRef

14.

Gaudiello I, Zibetti E, Lefort S, Chetouani M, Ivaldi S (2016) Trust as indicator of robot functional and social acceptance. An experimental study on user conformation to iCub answers. Comput Hum Behav 61:633–655CrossRef

15.

Chidambaram V, Chiang Y-H, Mutlu B (2012) Designing persuasive robots: how robots might persuade people using vocal and nonverbal cues. In: Proceedings of the seventh annual ACM/IEEE international conference on human–robot interaction, Boston, Massachusetts, USA, March 5–8 2012. ACM, pp 293–300

16.

Hirano T, Shiomi M, Iio T, Kimoto M, Tanev I, Shimohara K, Hagita N (2018) How do communication cues change impressions of human–robot touch interaction? Int J Soc Robot 10(1):21–31CrossRef

17.

Fong T, Nourbakhsh I, Dautenhahn K (2003) A survey of socially interactive robots. Robot Auton Syst 42(3–4):143–166CrossRef

18.

Mori M (1970) The uncanny valley. Energy 7(4):33–35

19.

Crumpton J, Bethel CL (2016) A survey of using vocal prosody to convey emotion in robot speech. Int J Soc Robot 8(2):271–285CrossRef

20.

Dou X, Wu C-F, Lin K-C, Tseng T-M (2019) The effects of robot voice and gesture types on the perceived robot personalities. In: International conference on human–computer interaction, 2019. Springer, pp 299–309

21.

Crowelly CR, Villanoy M, Scheutzz M, Schermerhornz P (2009) Gendered voice and robot entities: perceptions and reactions of male and female subjects. In: 2009 IEEE/RSJ international conference on intelligent robots and systems, 2009. IEEE, pp 3735–3741

22.

Siegel M, Breazeal C, Norton MI (2009) Persuasive robotics: The influence of robot gender on human behavior. In: 2009 IEEE/RSJ international conference on intelligent robots and systems, St Louis, US, 2009. IEEE, pp 2563–2568. https://doi.org/10.1109/iros.2009.5354116

23.

Usui T, Kume K, Yamano M, Hashimoto M (2008) A robotic KANSEI communication system based on emotional synchronization. In: 2008 IEEE/RSJ international conference on intelligent robots and systems, IROS, pp 3344–3349. https://doi.org/10.1109/iros.2008.4651172

24.

Aziz AA, Moganan FFM, Ismail A, Lokman AM (2015) Autistic children’s Kansei responses towards humanoid–robot as teaching mediator. Procedia Comput Sci 76:488–493. https://doi.org/10.1016/j.procs.2015.12.322CrossRef

25.

Mitsuo N (2002) Kansei engineering as a powerful consumer-oriented technology for product development. Appl Ergon 33:289–294CrossRef

26.

Kanda T, Ishiguro H, Ishida T (2001) Psychological analysis on human–robot interaction. In: IEEE international conference on robotics and automation Seoul, Korea, 2001. IEEE, Seoul, Korea, pp 21–26

27.

Mitsunaga N, Miyashita Z, Shinozawa K, Miyashita T, Ishiguro H, Hagita N (2008) What makes people accept a robot in a social environment—discussion from six-week study in an office. In: IEEE/RSJ international conference on intelligent robots and systems, 2008. IEEE, pp 3336–3343. https://doi.org/10.1109/iros.2008.4650785

28.

Robinson H, MacDonald B, Broadbent E (2014) The role of healthcare robots for older people at home: a review. Int J Soc Robot. https://doi.org/10.1007/s12369-014-0242-2CrossRef

29.

Beer JM, Liles KR, Wu X, Pakala S (2017) Affective human–robot interaction. In: Jeon M (ed) Emotions and affect in human factors and human–computer interaction. Academic Press, Cambridge. https://doi.org/10.1016/B978-0-12-801851-4.00015-XCrossRef

30.

Bertacchini F, Bilotta E, Pantano P (2017) Shopping with a robotic companion. Comput Hum Behav. https://doi.org/10.1016/j.chb.2017.02.064CrossRef

31.

Kim C, Kim D, Yuan J, Hill RB, Doshi P, Thai CN (2015) Robotics to promote elementary education pre-service teachers’ STEM engagement, learning, and teaching. Comput Educ. https://doi.org/10.1016/j.compedu.2015.08.005CrossRef

32.

Sheridan TB (2016) Human–robot interaction. Hum Factors 58:525–532. https://doi.org/10.1177/0018720816644364CrossRef

33.

Rau PLP, Li Y, Li D (2010) A cross-cultural study: effect of robot appearance and task. Int J Soc Robot. https://doi.org/10.1007/s12369-010-0056-9CrossRef

34.

Savela N, Turja T, Oksanen A (2018) Social acceptance of robots in different occupational fields: a systematic literature review. Int J Soc Robot 10(4):493–502. https://doi.org/10.1007/s12369-017-0452-5CrossRef

35.

Komatsubara T, Shiomi M, Kanda T, Ishiguro H (2018) Can using pointing gestures encourage children to ask questions? Int J Soc Robot 10(4):387–399. https://doi.org/10.1007/s12369-017-0444-5CrossRef

36.

Lohse M, Hegel F, Wrede B (2008) Domestic applications for social robots—an online survey on the influence of appearance and capabilities. J Phys Agents 2:21–32. https://doi.org/10.14198/JoPha.2008.2.2.04CrossRef

37.

Tigue CC, Borak DJ, O’Connor JJ, Schandl C, Feinberg DR (2012) Voice pitch influences voting behavior. Evol Human Behav 33(3):210–216. https://doi.org/10.1016/j.evolhumbehav.2011.09.004CrossRef

38.

Niculescu A, van Dijk B, Nijholt A, Li H, See SL (2013) Making social robots more attractive: the effects of voice pitch, humor and empathy. Int J Soc Robot 5(2):171–191. https://doi.org/10.1007/s12369-012-0171-xCrossRef

39.

Cheng YC (1997) The transformational leadership for school effectiveness and development in the New Century, p 34

40.

Lee EJ, Nass C, Brave S (2000) Can computer-generated speech have gender? An experimental test of gender stereotype. In: CHI’00 extended abstracts on Human factors in computing systems, Hague, Netherlands 2000. ACM, pp 289–290. https://doi.org/10.1145/633292.633461

41.

Walters M, Syrdal DS, Koay KL, Dautenhahn K, Te Boekhorst R (2008) Human approach distances to a mechanical-looking robot with different robot voice styles. In: Proceedings of the 17th IEEE international symposium on robot and human interactive communication, RO-MAN. https://doi.org/10.1109/roman.2008.4600750

42.

Laver J, John L (1994) Principles of phonetics. Cambridge University Press, CambridgeCrossRef

43.

Kent R (1976) Anatomical and neuromuscular maturation of the speech mechanism: evidence from acoustic studies. J Speech Hear Res 19(3):421–447MathSciNetCrossRef

44.

Warhurst S, Madill C, McCabe P, Ternström S, Yiu E, Heard R (2017) Perceptual and acoustic analyses of good voice quality in male radio performers. J Voice 31(2):e251–e259. https://doi.org/10.1016/j.jvoice.2016.05.016CrossRef

45.

Li J, Peng H, Hu H, Luo Z, Tang C (2018) Multimodal information fusion for automatic aesthetics evaluation of robotic dance poses. Int J Soc Robot. https://doi.org/10.1007/s12369-019-00535-wCrossRef

46.

Takeuchi J, Kushida K, Nishimura Y, Dohi H, Ishizuka M, Nakano M, Tsujino H (2006) Comparison of a humanoid robot and an on-screen agent as presenters to audiences. In: IEEE/RSJ international conference on intelligent robots and systems, Beijing, China, 2006. IEEE, pp 3964–3969. https://doi.org/10.1109/iros.2006.28183247

47.

Hendriks B, Meerbeek B, Boess S, Pauws S, Sonneveld M (2011) Robot vacuum cleaner personality and behavior. Int J Soc Robot 3(2):187–195. https://doi.org/10.1007/s12369-010-0084-5CrossRef

48.

Hwang J, Park T, Hwang W (2013) The effects of overall robot shape on the emotions invoked in users and the perceived personalities of robot. Appl Ergon 44(3):459–471. https://doi.org/10.1016/j.apergo.2012.10.010CrossRef

49.

Chatley AR, Dautenhahn K, Walters ML, Syrdal DS, Christianson B (2010) Theatre as a discussion tool in human–robot interaction experiments. A pilot study. In: 3rd international conference on advances in computer–human interactions. ACHI 2010. https://doi.org/10.1109/achi.2010.17

50.

Nørskov M (2017) Social robots: boundaries, potential, challenges. Taylor & Francis, LondonCrossRef

51.

Boersma P (2002) Praat, a system for doing phonetics by computer. Glot Int 5:341–345

52.

Niculescu A, Van Dijk B, Nijholt A, See SL (2011) The influence of voice pitch on the evaluation of a social robot receptionist. In: 2011 international conference on user science and engineering (i-USEr), Selangor, Malaysia, 2011. IEEE, Selangor, Malaysia, pp 18–23

53.

Rosenberg S, Nelson C, Vivekananthan PS (1968) A multidimensional approach to the structure of personality impressions. J Personal Soc Psychol 9(4):283CrossRef

54.

Fiske ST, Cuddy AJC, Glick P (2007) Universal dimensions of social cognition: warmth and competence. Trends Cogn Sci 11:77–83. https://doi.org/10.1016/j.tics.2006.11.005CrossRef

55.

Ybarra O, Chan E, Park DJM (2001) Young and old adults’ concerns about morality and competence. Motiv Emot 25(2):85–100CrossRef

56.

Nass C, Lee KM (2000) Does computer-generated speech manifest personality? An experimental test of similarity-attraction. In: Proceedings of the SIGCHI conference on Human factors in computing systems—CHI ‘00, Hague, Netherlands, April 2000. ACM, pp 329–336. https://doi.org/10.1145/332040.332452

57.

Shimp TA (1997) Advertising, promotion, and supplemental aspects of integrated marketing communications. Harcourt Brace College Publishers, Fort Worth

58.

Chad E, Autumn E, Patric RS, Lin X (2018) I, teacher: using artificial intelligence (AI) and social robots in communication and instruction. Commun Educ 67(4):473–480CrossRef

59.

Boring A (2017) Gender biases in student evaluations of teaching. J Public Econ 145:27–41. https://doi.org/10.1016/j.jpubeco.2016.11.006CrossRef

60.

Aaltonen I, Arvola A, Heikkilä P, Lammi H (2017) Hello Pepper, may i tickle you? Children’s and adults’ responses to an entertainment robot at a shopping mall. In: Proceedings of the companion of the 2017 ACM/IEEE international conference on human–robot interaction, pp 53–54. https://doi.org/10.1145/3029798.3038362

Title: Effects of Different Types of Social Robot Voices on Affective Evaluations in Different Application Fields
Authors: Xiao Dou
Chih-Fu Wu
Kai-Chieh Lin
Senzhong Gan
Tzu-Min Tseng
Publication date: 22-05-2020
Publisher: Springer Netherlands
Published in: International Journal of Social Robotics / Issue 4/2021
Print ISSN: 1875-4791
Electronic ISSN: 1875-4805
DOI: https://doi.org/10.1007/s12369-020-00654-9

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