Abstract
This paper is dedicated to modeling affective reactions in a communicative robot via achieving communicative goals. The effective robot F-2’s software processes multimodal input and facts extracted from input texts. Sentences in Russian are translated with a syntactic-semantic parser into semantic structures that represent sentences meanings and comprise valencies and semantic markers. Basing on the input, the robot changes its emotional state over time, generating effective remarks along with gestures and gazes. The emotional state is modeled via microstates, each represented as a communicative goal, which is further matched to multimodal reactions scenarios from a database. New communicative strategies are introduced. Basing on human features extraction from video, a robot implements strategies of complimenting and making friends; in both cases, it points at the addressee’s look, including clothes and glasses. With tactile sensors, the robot is taught to react to touching; thus the gap in perception is filled which had previously caused the loss of interest by people inclined to tactile communication. Precision is estimated for both methods which are on the basis of new communicative strategies.
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References
Allen, S.R.: Concern processing in autonomous agents, Ph.D. thesis. The University of Birmingham, Birmingham (2001)
Almansor, E.H., Hussain, F.K.: Survey on intelligent chatbots: state-of-the-art and future research directions. In: Barolli, L., Hussain, F.K., Ikeda, M. (eds.) CISIS 2019. AISC, vol. 993, pp. 534–543. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-22354-0_47
Becker, C., Kopp, S., Wachsmuth, I.: Simulating the emotion dynamics of a multimodal conversational agent. In: André, E., Dybkjær, L., Minker, W., Heisterkamp, P. (eds.) ADS 2004. LNCS (LNAI), vol. 3068, pp. 154–165. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-24842-2_15
Breazeal, C.: Designing Sociable Robots. MIT Press, Cambridge (2002)
Cai, Y.: Empathic computing. In: Cai, Y., Abascal, J. (eds.) Ambient Intelligence in Everyday Life. LNCS (LNAI), vol. 3864, pp. 67–85. Springer, Heidelberg (2006). https://doi.org/10.1007/11825890_3
COCO dataset (2021). https://cocodataset.org/. Accessed 20 Mar 2021
Engleberg, I.N., Wynn, D.R.: Working in Groups: Communication Principles and Strategies. My Communication Kit Series, p. 133. Allyn & Bacon, Boston (2006)
F-2 standby, NRCKI cognitive team (2019). http://youtube.com/watch?v=TrKh5xohBZg. Accessed 15 April 2019
Fung, P., et al.: Towards empathetic human-robot interactions. In: Gelbukh, A. (ed.) CICLing 2016. LNCS, vol. 9624, pp. 173–193. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-75487-1_14
Girshick, R.: Fast R-CNN. In: IEEE International Conference on Computer Vision (ICCV), 2015, pp. 1440–1448. IEEE, Pictasaway (2015)
Greta, Embodied Conversational Agent (2017). http://perso.telecomparistech.fr/~pelachau/Greta/. Accessed 10 April 2017
Halawa, L.J., Wibowo, A., Ernawan, F.: Face recognition using faster R-CNN with inception-V2 architecture for CCTV camera. In: 2019 3rd International Conference on Informatics and Computational Sciences (ICICoS), pp. 1–6. IEEE, Pictasaway (2019)
Han, J.G., Campbell, N., Jokinen, K., Wilcock, G.: Investigating the use of non-verbal cues in human-robot interaction with a Nao robot. In: Proceedings of the 3rd IEEE International Conference on Cognitive Infocommunications (CogInfoCom 2012), Kosice, Slovakia, pp. 679–683. IEEE, Pictasaway (2012)
I·bug (2017). http://ibug.doc.ic.ac.uk/. Accessed 10 April 2017
InterLink Electronics. FSR 400 series (2020). https://www.interlinkelectronics.com/fsr-400-series. Accessed 18 July 2020
Iwashita, M., Katagami, D.: Psychological effects of compliment expressions by communication robots on humans. In: 2020 International Joint Conference on Neural Networks (IJCNN), pp. 1–8. IEEE, Piscataway (2020). https://doi.org/10.1109/IJCNN48605.2020.9206898
Jokinen, K., Wilcock, G.: Modelling user experience in human-robot interactions. In: MA3HMI 2014 Workshop, LNAI, vol. 8757, pp. 45–56. Springer, Heidelberg (2014)
Kirby, R., Forlizzi, J., Simmons, R.: Affective social robots. Robot. Auton. Syst. 58, 322–332. Elsevier, Amsterdam (2010)
Kopp, S.: Social resonance and embodied coordination in face-to-face conversation with artificial interlocutors. Speech Commun. 52, 587–597. Elsevier, Amsterdam (2010)
Kotov, A.A.: Patterns of emotional communicative reactions: problems of creating a corpus and translating to emotional agents (in Russian). In: Computational Linguistics and Intellectual Technologies, vol. 8, pp. 211–218. RSUH, Moscow (2009)
Kotov, A.A., Zinnia, A.A.: Functional analysis of non-verbal communicative behavior (in Russian). In: Computational Linguistics and Intellectual Technologies, vol. 14, no. 2, pp. 308–320. RSUH, Moscow (2015)
Max (2017). http://cycling74.com/products/max/. Accessed 10 April 2017
Minsky, M.: A framework for representing knowledge. In: Patrick Henry Winston (ed.) The Psychology of Computer Vision. McGraw-Hill, New York (1975)
Mori, M.: The uncanny valley (K. F. MacDorman & N. Kageki, Trans.). IEEE Robot. Autom. Mag. 19(2), 98–100 (1970/2012)
Neonode AirBar (2020). https://air.bar/. Accessed 18 July 2020
Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. In: IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39. IEEE, Pictasaway (2015)
Rudakov, I.V., Paschenkova, A.V.: A hierarchical method for verification of software algorithms via hierarchical Petri nets. Engineering Journal: Science and Innovations, vol. 2, no. 14 (in Russian). BMSTU Press, Moscow (2013). https://doi.org/10.18698/2308-6033-2013-2-538
Russell, J.: Core affect and the psychological construction of emotion. Psychol. Rev. 110(1), 145–172. American Psychological Association, Washington (2003)
Semaine Project (2017). http://www.semaine-project.eu/. Accessed 10 April 2017
Sloman, A., Chrisley, R.: Virtual machines and consciousness. J. Conscious. Stud. 10(4–5), 133–172. Imprint Academic, Exeter (2003)
Shröder, M.: The SEMAINE API: towards a standards-based framework for building emotion-oriented systems. Adv. Hum.-Comput. Interact. 2010, 319406. Hindawi, London (2010)
TonTek TTP223-BA6_SPEC_V2.1 (2020). https://static.chipdip.ru/lib/949/DOC005949559.pdf. Accessed 27 Dec 2020
Vilhjálmsson, H., et al.: The behavior markup language: recent developments and challenges. In: Pelachaud, C., Martin, J.-C., André, E., Chollet, G., Karpouzis, K., Pelé, D. (eds.) IVA 2007. LNCS (LNAI), vol. 4722, pp. 99–111. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-74997-4_10
Vinyals, O., Le, Q.: A neural conversational model. In: Proceedings of ICML Deep Learning Workshop, July 2015. https://arxiv.org/abs/1506.05869. Accessed 15 April 2019
Viola, P., Jones, M.: Robust real-time face detection. Int. J. Comput. Vis. 57, 137–154 (2004). https://doi.org/10.1023/B:VISI.0000013087.49260.fb
Volkova, L., Kotov, A., Klyshinsky, E., Arinkin, N.: A robot commenting texts in an emotional way. In: Kravets, A., Shcherbakov, M., Kultsova, M., Groumpos, P. (eds.) CIT&DS 2017. CCIS, vol. 754, pp. 256–266. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-65551-2_19
Weiss, K., Khoshgoftaar, T.M., Wang, D.: A survey of transfer learning. J. Big Data, vol. 3. Springer, Heidelberg (2016)
Weizenbaum, J.: ELIZA. Commun. ACM 9, 36–45 (1966)
Winograd, T.: Understanding Natural Language. Academic Press, New York (1972)
Yandex SpeechKit API (in Russian). http://api.yandex.ru/speechkit/. Accessed 10 April 2017
Zhou, L., Gao, J., Li, D., Shum, H.-Y.: The Design and Implementation of XiaoIce, an Empathetic Social Chatbot (2018–12–21). https://arxiv.org/abs/1812.08989. Accessed 15 April 2019
Zou, L., Ge, C., Wang, Z., Cretu, E., Li, X.: Novel tactile sensor technology and smart tactile sensing systems: a review. Sensors 17(11), 2653. MDPI, Basel (2017)
Acknowledgments
This research is supported by the grant of the Russian Science Foundation (project № 19–18-00547).
The F-2 team wishes to express gratitude to all of our respondents, including students of the Power Engineering department of BMSTU. All of the feedback is precious for us as it shows new directions of further development for F-2.
We also wish to thank our colleague Edward Klyshinsky for pointing out Azimov’s “Sally” short story for epigraphs, an inspiration to beam this article with.
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Volkova, L., Ignatev, A., Kotov, N., Kotov, A. (2021). New Communicative Strategies for the Affective Robot: F-2 Going Tactile and Complimenting. In: Kravets, A.G., Shcherbakov, M., Parygin, D., Groumpos, P.P. (eds) Creativity in Intelligent Technologies and Data Science. CIT&DS 2021. Communications in Computer and Information Science, vol 1448. Springer, Cham. https://doi.org/10.1007/978-3-030-87034-8_13
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