Abstract
In this paper, we investigate to what extent tutors’ behavior is influenced by different kinds of robot feedback. In particular, we study the effects of online robot feedback in which the robot responds either contingently to the tutor’s social behavior or by tracking the objects presented. Also, we investigate the impact of the robot’s learning success on tutors’ tutoring strategies. Our results show that only in the condition in which the robot’s behavior is socially contingent, the human tutors adjust their behavior to the robot. In the developmentally equally plausible object-driven condition, in which the robot tracked the objects presented, tutors do not change their behavior significantly, even though in both conditions the robot develops from a prelinguistic stage to producing keywords. Socially contingent robot feedback has thus the potential to influence tutors’ behavior over time. Display of learning outcomes, in contrast, only serves as feedback on robot capabilities when it is coupled with online social feedback.
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References
Wrede, B., Schillingmann, L., Rohlfing, K.J.: Making Use of Multi-Modal Synchrony: A Model of Acoustic Packaging to Tie Words to Actions, ch. 10, pp. 224–240. IGI Global, Hershey (2013)
Fernald, A., Weisleder, A.: Early language experience is vital to developing fluency in understanding. In: Neuman, S., Dickinson, D. (eds.) Handbook of Early Literacy Research, vol. 3. Guiltford Publications, New York (2011)
Gergely, G., Watson, J.: Early socio-emotional development: Contingency perception and the social-biofeedback model. In: Early Social Cognition: Understanding Others in the First Months of Life, pp. 101–136 (1999)
Watson, J.: Contingency perception in early social development. Social Perception in Infants, 157–176 (1985)
Csibra, G.: Recognizing communicative intentions in infancy. Mind & Language 25(2), 141–168 (2010)
Nourbakhsh, I., Kunz, C., Willeke, T.: The mobot museum robot installations: A five year experiment. In: Proceedings of the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems, Las Vegas, Nevada, pp. 3636–3641 (October 2003)
Sidner, C., Lee, C., Kidd, C., Lesh, N., Rich, C.: Explorations in engagement for humans and robots. Artificial Intelligence 166(1-2), 140–164 (2005)
Yoshikawa, Y., Shinozawa, K., Ishiguro, H.: Social reflex hypothesis on blinking interaction. In: Proceedings of the 29th Annual Conference of the Cognitive Science Society, pp. 725–730 (2007)
Breazeal, C.: Toward sociable robots. Robotics and Autonomous Systems 42(3), 167–175 (2003)
Kose-Bagci, H., Broz, F., Shen, Q., Dautenhahn, K., Nehaniv, C.L.: As time goes by: Representing and reasoning about timing in human-robot interaction studies. In: AAAI Spring Symposium: It’s All in the Timing (2010)
Lohan, K.S., Rohlfing, K.J.R., Pitsch, K., Saunders, J., Lehmann, H., Nehaniv, C.L., Fischer, K., Wrede, B.: Tutor spotter: Proposing a feature set and evaluating it in a robotic system. International Journal of Social Robotics 4(2), 131–146 (2012)
Fischer, K., Lohan, K.S., Saunders, J., Nehaniv, C., Wrede, B., Rohlfing, K.: The impact of the contingency of robot feedback on HRI. In: International Conference on Cooperative Technological Systems (CTS 2013), San Diego, May 20-24 (2013)
Fischer, K., Saunders, J.: Getting acquainted with a developing robot. In: Salah, A.A., Ruiz-del-Solar, J., Meriçli, Ç., Oudeyer, P.-Y. (eds.) HBU 2012. LNCS, vol. 7559, pp. 125–133. Springer, Heidelberg (2012)
Metta, G., Natale, L., Nori, F., Sandini, G., Vernon, D., Fadiga, L., Von Hofsten, C., Rosander, K., Lopes, M., Santos-Victor, J., et al.: The icub humanoid robot: An open-systems platform for research in cognitive development. Neural Networks 23(8), 1125–1134 (2010)
Lohan, K., Pitsch, K., Rohlfing, K., Fischer, K., Saunders, J., Lehmann, H., Nehaniv, C., Wrede, B.: Contingency allows the robot to spot the tutor and to learn from interaction. In: ICDL-EpiRob 2011 (2011)
Matatyaho, D., Gogate, L.: Type of maternal object motion during synchronous naming predicts preverbal infants’ learning of word–object relations. Infancy 13(2), 172–184 (2008)
Gogate, L., Bolzani, L., Betancourt, E.: Attention to maternal multimodal naming by 6-to 8-month-old infants and learning of word–object relations. Infancy 9(3), 259–288 (2006)
de Barbaro, K., Johnson, C.M., Forster, D., Deak, G.O.: Temporal dynamics of multimodal multiparty interactions: A micrognesis of early social interaction. In: Spink, A., et al. (eds.) Proceedings of Measuring Behavior 2010, Eindhoven, The Netherlands, pp. 247–249 (2010)
Saunders, J., Nehaniv, C.L., Lyon, C.: Robot learning of lexical semantics from sensorimotor interaction and the unrestricted speech of human tutors. In: Proc. Second International Symposium on New Frontiers in Human-Robot Interaction, AISB Convention, Leicester, UK (2010)
Saunders, J., Lehmann, H., Sato, Y., Nehaniv, C.L.: Towards using prosody to scaffold lexical meaning in robots. In: Proceedings of ICDL-EpiRob 2011. IEEE (2011)
Fischer, K., Lohan, K., Foth, K.: Levels of embodiment: Linguistic analyses of factors influencing HRI. In: Proceedings of HRI 2012, Boston, Mass., MA (March 2012)
Chung, C.K., Pennebaker, J.W.: The psychological function of function words. In: Fiedler, K. (ed.) Social Communication: Frontiers of Social Psychology, pp. 343–359. Psychology Press, New York (2007)
Horton, W.S., Gerrig, R.J.: The impact of memory demands on audience design during language production. Cognition 96, 127–142 (2005)
Cross, T.G., Nienhuys, T.G., Kirkman, M.: Parent–child interaction with receptively disabled children: Some determinants of maternal speech style. In: Nelson, K. (ed.) Children’s Language, vol. 5, pp. 247–290. Erlbaum, Hillsdale (1985)
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Fischer, K., Lohan, K.S., Nehaniv, C., Lehmann, H. (2013). Effects of Different Kinds of Robot Feedback. In: Herrmann, G., Pearson, M.J., Lenz, A., Bremner, P., Spiers, A., Leonards, U. (eds) Social Robotics. ICSR 2013. Lecture Notes in Computer Science(), vol 8239. Springer, Cham. https://doi.org/10.1007/978-3-319-02675-6_26
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DOI: https://doi.org/10.1007/978-3-319-02675-6_26
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02674-9
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