DualKeepon: a human–robot interaction testbed to study linguistic features of speech


In this paper, we present a novel dual-robot testbed called DualKeepon for carrying out pairwise comparisons of linguistic features of speech in human–robot interactions. Our solution, using a modified version of the MyKeepon robotic toy developed by Beatbots, is a portable open-source system for researchers to set up experiments quickly, and in an intuitive way. We provide an online tutorial with all required materials to replicate the system. We present two human–robot interaction studies to demonstrate the testbed. The first study investigates the perception of robots using filled pauses. The second study investigates how social roles, realized by different prosodic and lexical speaking profiles, affect trust. Results show that the proposed testbed is a helpful tool for linguistic studies. In addition to the basic setup, advanced users of the system have the ability to connect the system to different robot platforms, i.e., NAO, Pepper.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10


  1. 1.

    The ‘Hacking Keepon’ workshop at the 2013 International Summer School on Social HRI for a multidisciplinary group of researchers.

  2. 2.


  3. 3.


  4. 4.


  5. 5.


  6. 6.

    Bridge version: (https://github.com/hoanglongcao/DualKeepon/tree/master/Bridge%20version).


  1. 1.

    Aarestrup M, Jensen LC, Fischer K (2015) The sound makes the greeting: interpersonal functions of intonation in human–robot interaction. In: 2015 AAAI spring symposium series. AAAI, Palo Alto, California, USA, pp 67–70

  2. 2.

    Andrist S, Spannan E, Mutlu B (2013) Rhetorical robots: making robots more effective speakers using linguistic cues of expertise. In: Proceedings of the 8th ACM/IEEE international conference on human–robot interaction (HRI). IEEE Press, Tokyo, Japan, pp 341–348

  3. 3.

    Andrist S, Ziadee M, Boukaram H, Mutlu B, Sakr M (2015) Effects of culture on the credibility of robot speech: a comparison between English and Arabic. In: Proceedings of the 10th annual ACM/IEEE international conference on human–robot interaction (HRI). ACM, Portland, Oregon, USA, pp 157–164

  4. 4.

    Asselborn TLC, Johal W, Dillenbourg P (2017) Keep on moving! exploring anthropomorphic effects of motion during idle moments. In: 26th IEEE international symposium on robot and human interactive communication (ROMAN). IEEE, Lisbon, Portugal, pp 897–902

  5. 5.

    Azmin AF, Shamsuddin S, Yussof H (2016) HRI observation with My Keepon robot using Kansei engineering approach. In: 2016 2nd IEEE international symposium on robotics and manufacturing automation (ROMA). IEEE, Ipoh, Malaysia, pp 1–6

  6. 6.

    Azuma J (2006) Creating micro exercises utilizing text-to-speech technology: new horizons in foreign language teaching. In: Hug T, Lindner M, Bruck PA (eds) Micromedia and e-learning 2.0: gaining the big picture. Innsbruck University Press, Austria, pp 198–210

  7. 7.

    Bainbridge WA, Hart JW, Kim ES, Scassellati B (2011) The benefits of interactions with physically present robots over video-displayed agents. Int J Soc Robot 3(1):41–52

    Article  Google Scholar 

  8. 8.

    Baxter P, Ashurst E, Read R, Kennedy J, Belpaeme T (2017) Robot education peers in a situated primary school study: personalisation promotes child learning. PloS one 12(5):e0178126

    Article  Google Scholar 

  9. 9.

    Baxter P, Kennedy J, Senft E, Lemaignan S, Belpaeme T (2016) From characterising three years of HRI to methodology and reporting recommendations. In: 11th ACM/IEEE international conference on human robot interaction (HRI). IEEE Press, New York, USA, pp 391–398

  10. 10.

    Bethel CL, Murphy RR (2010) Review of human studies methods in HRI and recommendations. Int J Soc Robot 2(4):347–359

    Article  Google Scholar 

  11. 11.

    Betz S, Carlmeyer B, Wagner P, Wrede B (2018) Interactive hesitation synthesis: modelling and evaluation. Multimodal Technol Interact 2(1):1–21

    Article  Google Scholar 

  12. 12.

    Breazeal C, Harris PL, DeSteno D, Westlund K, Jacqueline M, Dickens L, Jeong S (2016) Young children treat robots as informants. Top Cogn Sci 8(2):481–491

    Article  Google Scholar 

  13. 13.

    Bresnahan MJ, Ohashi R, Nebashi R, Liu WY, Shearman SM (2002) Attitudinal and affective response toward accented english. Lang Commun 22(2):171–185

    Article  Google Scholar 

  14. 14.

    Brown L, Howard AM (2013) Engaging children in math education using a socially interactive humanoid robot. In: 2013 13th IEEE-RAS international conference on humanoid robots (Humanoids). IEEE, Atlanta, GA, USA, pp 183–188

  15. 15.

    Cao HL, Van de Perre G, Simut R, Pop C, Peca A, Lefeber D, Vanderborght B (2014) Enhancing My Keepon robot: a simple and low-cost solution for robot platform in human–robot interaction studies. In: 23rd IEEE international symposium on robot and human interactive communication (RO-MAN). IEEE, Edinburgh, UK, pp 555–560

  16. 16.

    Cao HL, Pop C, Simut R, Furnémont R, De Beir A, Van de Perre G, Esteban PG, Lefeber D, Vanderborght B (2015) Probolino: a portable low-cost social device for home-based autism therapy. In: International conference on social robotics. Springer, Paris, France, pp 93–102

  17. 17.

    Carlmeyer B, Betz S, Wagner P, Schlangen D, Wrede B (2018) The hesitating robot—implementation and first impressions. In: Companion of the 2018 ACM/IEEE international conference on human–robot interaction (HRI). ACM, New York, USA, pp 1–2

  18. 18.

    Clopper CG, Pisoni DB (2002) Perception of dialect variation: some implications for current research and theory in speech perception. Research on spoken language processing progress report, vol 25. Indiana University Press, Indiana, USA, pp 270–190

  19. 19.

    Costescu CA, Vanderborght B, David DO (2015) Reversal learning task in children with autism spectrum disorder: a robot-based approach. J Autism Dev Disord 45(11):3715–3725

    Article  Google Scholar 

  20. 20.

    Costescu CA, Vanderborght B, David DO (2017) Robot-enhanced CBT for dysfunctional emotions in social situations for children with ASD. J Evid Based Psychother 17(2):119–132

    Article  Google Scholar 

  21. 21.

    Docan-Morgan T, Manusov V, Harvey J (2013) When a small thing means so much: nonverbal cues as turning points in relationships. Interpersona 7(1):110–124

    Article  Google Scholar 

  22. 22.

    Dow S, MacIntyre B, Lee J, Oezbek C, Bolter JD, Gandy M (2005) Wizard of oz support throughout an iterative design process. IEEE Pervasive Comput 4(4):18–26

    Article  Google Scholar 

  23. 23.

    Fasola J, Mataric M (2013) A socially assistive robot exercise coach for the elderly. J Hum Robot Interact 2(2):3–32

    Article  Google Scholar 

  24. 24.

    Fischer K (2000) From cognitive semantics to lexical pragmatics: the functional polysemy of discourse particles. Walter de Gruyter, Berlin

    Google Scholar 

  25. 25.

    Fischer K (2016) Robots as confederates: how robots can and should support research in the humanities. In: Proceedings of the 2016 robophilosophy conference. IOS Press, Aarhus, Denmark, pp 60–66

  26. 26.

    Fischer K, Lohan K, Foth K (2012) Levels of embodiment: linguistic analyses of factors influencing HRI. In: Proceedings of the 7th ACM/IEEE international conference on human–robot interaction (HRI). IEEE, Boston, MA, USA, pp 463–470

  27. 27.

    Fischer K, Niebuhr O, Novák-Tót E, Jensen LC (2017) Strahlt die negative reputation von häsitationsmarkern auf ihre sprecher aus? In: Proceedings of the 43rd annual meeting of the German acoustical society (DAGA). Kiel, Germany, pp 1450–1453

  28. 28.

    Fox Tree JE (2002) Interpreting pauses and ums at turn exchanges. Discourse Process 34(1):37–55

    Article  Google Scholar 

  29. 29.

    Gallois C, Giles H (2015) Communication accommodation theory. In: Tracy K, Sandel T, Ilie C (eds) The international encyclopedia of language and social interaction. Wiley, Hoboken, pp 1–18

    Google Scholar 

  30. 30.

    Henton C (2012) Text-to-speech synthesis development. In: Chapelle CA (ed) The encyclopedia of applied linguistics. Wiley, Hoboken, pp 1–6

    Google Scholar 

  31. 31.

    Holmes J, Hazen K (2014) Research methods in sociolinguistics: a practical guide, vol 5. Wiley, Hoboken

    Google Scholar 

  32. 32.

    Hood D, Lemaignan S, Dillenbourg P (2015) When children teach a robot to write: an autonomous teachable humanoid which uses simulated handwriting. In: Proceedings of the 10th annual ACM/IEEE international conference on human–robot interaction (HRI). ACM, Portland, Oregon, USA, pp 83–90

  33. 33.

    Kanda T, Hirano T, Eaton D, Ishiguro H (2004) Interactive robots as social partners and peer tutors for children: a field trial. Hum Comput Interact 19(1/2):61–84

    Article  Google Scholar 

  34. 34.

    Kircher R (2015) The matched-guise technique. In: Hua Z (ed) Research methods in intercultural communication: a practical guide. John Wiley & Sons Inc, Hoboken, NJ, pp 196–211

    Google Scholar 

  35. 35.

    Kuhlen AK, Brennan SE (2013) Language in dialogue: when confederates might be hazardous to your data. Psychon Bull Rev 20(1):54–72

    Article  Google Scholar 

  36. 36.

    Lambert WE, Hodgson RC, Gardner RC, Fillenbaum S (1960) Evaluational reactions to spoken languages. J Abnorm Soc Psychol 60(1):44

    Article  Google Scholar 

  37. 37.

    Levinson SC (1983) Pragmatics. Cambridge University Press, New York

    Google Scholar 

  38. 38.

    Leyzberg D, Spaulding S, Scassellati B (2014) Personalizing robot tutors to individuals’ learning differences. In: Proceedings of the 2014 ACM/IEEE international conference on human–robot interaction (HRI). ACM, Bielefeld, Germany, pp 423–430

  39. 39.

    Lund AM (2001) Measuring usability with the use questionnaire. Usability Interface 8(2):3–6

    Google Scholar 

  40. 40.

    Mangelsdorf K (1992) Peer reviews in the ESL composition classroom: what do the students think? ELT J 46(3):274–284

    Article  Google Scholar 

  41. 41.

    Meghdari A, Alemi M, Ghazisaedy M, Taheri A, Karimian A, Zandvakili M (2013) Applying robots as teaching assistant in EFL classes at Iranian middle-schools. In: International conference on education and modern educational technologies (EMET-2013). ADIS, Kuala Lumpur, Malaysia, pp 67–73

  42. 42.

    Mendonca CO, Johnson KE (1994) Peer review negotiations: revision activities in ESL writing instruction. TESOL Q 28(4):745–769

    Article  Google Scholar 

  43. 43.

    Mohammad Y, Ohya T, Hiramatsu T, Sumi Y, Nishida T (2007) Embodiment of knowledge into the interaction and physical domains using robots. In: International conference on control automation and systems (ICCAS), 2007. IEEE, Guangzhou, China, pp 737–744

  44. 44.

    Nelson GL, Murphy JM (1993) Peer response groups: do L2 writers use peer comments in revising their drafts? TESOL Q 27(1):135–141

    Article  Google Scholar 

  45. 45.

    Peca A, Simut R, Cao HL, Vanderborght B (2016) Do infants perceive the social robot Keepon as a communicative partner? Infant Behav Dev 42:157–167

    Article  Google Scholar 

  46. 46.

    Pfeifer R, Gómez G (2009) Morphological computation—connecting brain, body, and environment. In: Sendhoff B, Krner E, Sporns O, Ritter H, Doya K (eds) Creat Brain Like Intell. Springer, Berlin, pp 66–83

    Google Scholar 

  47. 47.

    Pisoni D, Remez R (2008) The handbook of speech perception. Wiley, Oxford

    Google Scholar 

  48. 48.

    Riek LD (2012) Wizard of oz studies in HRI: a systematic review and new reporting guidelines. J Hum Robot Interact 1(1):119–136

    Article  Google Scholar 

  49. 49.

    Robins B, Dautenhahn K, Dubowski J (2005) Robots as isolators or mediators for children with autism a cautionary tale. In: Proceedings of the AISB 05 symposium on robot companions. AISB, Hatfield, UK, pp 82–88

  50. 50.

    Rosenberg A, Hirschberg J (2009) Charisma perception from text and speech. Speech Commun 51(7):640–655

    Article  Google Scholar 

  51. 51.

    Solís Obiols M (2002) The matched guise technique: a critical approximation to a classic test for formal measurement of language attitudes. Noves SL. Rev Socioling 1:1–6

    Google Scholar 

  52. 52.

    Srinivasan V, Takayama L (2016) Help me please: Robot politeness strategies for soliciting help from humans. In: Proceedings of the 2016 CHI conference on human factors in computing systems. ACM, San Jose, CA, USA, pp 4945–4955

  53. 53.

    Strait M, Canning C, Scheutz M (2014) Let me tell you! Investigating the effects of robot communication strategies in advice-giving situations based on robot appearance, interaction modality and distance. In: Proceedings of the 2014 ACM/IEEE international conference on human–robot interaction (HRI). ACM, Bielefeld, Germany, pp 479–486

  54. 54.

    Strupka E, Niebuhr O, Fischer K (2016) Influence of robot gender and speaker gender on prosodic entrainment in HRI. In: Proceedings 25th IEEE robot and human interactive communication (RO-MAN). IEEE, New York City, USA, pp 1–2

  55. 55.

    Thill S, Pop CA, Belpaeme T, Ziemke T, Vanderborght B (2012) Robot-assisted therapy for autism spectrum disorders with (partially) autonomous control: challenges and outlook. Paladyn 3(4):209–217

    Google Scholar 

  56. 56.

    Toris R, Kent D, Chernova S (2014) The robot management system: a framework for conducting human–robot interaction studies through crowdsourcing. J Hum Robot Interact 3(2):25–49

    Article  Google Scholar 

  57. 57.

    Torrey C, Fussell S, Kiesler S (2013) How a robot should give advice. In: Proceedings of the 8th ACM/IEEE international conference on human–robot interaction (HRI). IEEE Press, Tokyo, Japan, pp 275–282

  58. 58.

    Walters ML, Woods S, Koay KL, Dautenhahn K (2005) Practical and methodological challenges in designing and conducting human–robot interaction studies. In: 2005 AISB symposium on robot companions. AISB

  59. 59.

    Whittaker S, O’Conaill B (1997) The role of vision in face-to-face and mediated communication. In: Finn KE, Sellen AJ, Wilbur SB (eds) Video-mediated communication. Lawrence Erlbaum Associates Publishers, Mahwah, pp 23–49

    Google Scholar 

  60. 60.

    Wigdor N, de Greeff J, Looije R, Neerincx MA (2016) How to improve human–robot interaction with conversational fillers. In: 25th IEEE international symposium on robot and human interactive communication (RO-MAN). IEEE, New York, USA, pp 219–224

  61. 61.

    Wolfgang A (2013) Nonverbal behavior: applications and cultural implications. Academic Press, New York

    Google Scholar 

  62. 62.

    Zaga C, Lohse M, Truong KP, Evers V (2015) The effect of a robot’s social character on children’s task engagement: peer versus tutor. In: International conference on social robotics. Springer, Paris, France, pp 704–713

Download references


The authors would like to acknowledge the helpful comments of the anonymous reviewers on the earlier versions of this paper. The work leading to these results has received funding from the EC FP7 project DREAM (grant no. 611391) and the ICON project ROBO-CURE.

Author information



Corresponding author

Correspondence to Hoang-Long Cao.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The authors H.-L. Cao and L.C. Jensen contributed equally to this work.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Cao, H., Jensen, L.C., Nghiem, X.N. et al. DualKeepon: a human–robot interaction testbed to study linguistic features of speech. Intel Serv Robotics 12, 45–54 (2019). https://doi.org/10.1007/s11370-018-0266-9

Download citation


  • Keepon
  • Social robot
  • Human–robot interaction
  • NAO
  • Low-cost robotics
  • Linguistics