ABSTRACT
This paper describes our proposal for enriching personalized social moments and dialogues between human and robot in the context of the Sugar, Salt & Pepper laboratory. The lab focused on the use of the Pepper robot in a therapeutic context to promote autonomies and functional acquisitions in highly functioning (Asperger) children with autism. This paper is focused on a post-hoc work aimed at improving the robot's autonomous dialogue strategies. In particular we are integrating the robot's dialogue with a knowledge base to have the robot able to move and reason on an ontology, and thus enriching its dialogue's strategies. For instance, the taxonomic structure of the ontology could allow Pepper to drive the focus of the conversation to related topics or to more general or specific topics, and, in general, it could improve its capability to manage the conversation and disambiguate the input from the user.
- Admoni, H., Scassellati, B.: Social eye gaze in human-robot interaction: A review. Journal of Human-Robot Interaction 6(1), 25–63 (2017)Google Scholar
- Aresti-Bartolome N, Garcia-Zapirain B. Technologies as support tools for persons with autistic spectrum disorder: a systematic review. Int J Environ Res Public Health. 2014 Aug 4;11(8):7767-802. doi: 10.3390/ijerph110807767. PMID: 25093654; PMCID: PMC4143832.Google Scholar
- Bocklisch, T., Faulkner, J., Pawlowski, N., & Nichol, A. (2017). RASA: Open source language understanding and dialogue management. arXiv preprint arXiv:1712.05181.Google Scholar
- Carmagnola, F., Cena, F., Gena, C. (2007). User Modeling in the Social Web. In: Apolloni, B., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2007. Lecture Notes in Computer Science(), vol 4694. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74829-8_91Google Scholar
- Brian Carr, Ira P. Goldstein. Overlays : a theory of modelling for computer aided instruction. 1977. (hal-00702959)Google Scholar
- Chevalier, P., Martin, J.C., Isableu, B., Bazile, C., Iacob, D.O., Tapus, A.: Joint attention using human-robot interaction: Impact of sensory preferences of children with autism. In: Robot and Human Interactive Communication (RO-MAN), 2016 25th IEEE International Symposium on. pp. 849–854. IEEE (2016)Google Scholar
- Corbett, A.T. and Anderson, J.R. (1994) ‘Knowledge tracing: modelling the acquisition of procedural knowledge’, User Modelling and User-Adapted Interaction, Vol. 4, No. 4, pp.253–278.Google Scholar
- Francisco de Souza, J., Siqueira, S. W., & Melo, R. N. (2011). Evolution in Ontology-Based User Modeling. In M. Lytras, P. Ordóñez de Pablos, & E. Damiani (Ed.), Semantic Web Personalization and Context Awareness: Management of Personal Identities and Social Networking (pp. 137-150). IGI Global. https://doi.org/10.4018/978-1-61520-921-7.ch011Google Scholar
- Rossana Damiano, Cristina Gena, Andrea Maieli, Claudio Mattutino, Alessandro Mazzei, Elisabetta Miraglio, Giulia Ricciardiello: UX Personas for defining robot's character and personality. 6. IUI Workshops 2022: 213-216, 2022Google Scholar
- Dautenhahn, I. Werry, Towards Interactive Robots in Autism Therapy: Background, Motivation and Chal-lenges, “Pragmatics & Cognition”, https://doi.org/10.1075/pc.12.1.03dau, 2004;Google Scholar
- V. Cietto, C. Gena, I. Lombardi, C. Mattutino and C. Vaudano, "Co-designing with kids an educational robot," 2018 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO), 2018, pp. 139-140, doi: 10.1109/ARSO.2018.8625810.Google ScholarDigital Library
- C. Gena, C. Mattutino, G. Perosino, M. Trainito, C. Vaudano and D. Cellie, "Design and Development of a Social, Educational and Affective Robot," 2020 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS), 2020, pp. 1-8, doi: 10.1109/EAIS48028.2020.9122778.Google Scholar
- Cristina Gena, Claudio Mattutino, Stefania Brighenti, Andrea Meirone, Francesco Petriglia, Loredana Mazzotta, Federica Liscio, Matteo Nazzario, Valeria Ricci, Camilla Quarato, Cesare Pecone, Giuseppe Piccinni: Sugar, Salt & Pepper - Humanoid robotics for autism. IUI Workshops 2021Google Scholar
- Cristina Gena, Claudio Mattutino, Andrea Maieli, Elisabetta Miraglio, Giulia Ricciardiello, Rossana Damiano, Alessandro Mazzei: Autistic Children's Mental Model of an Humanoid Robot. UMAP (Adjunct Publication) 2021: 128-129Google Scholar
- Cristina Gena, Claudio Mattutino, Stefania Brighenti, Matteo Nazzario: Social Assistive Robotics for Autistic Children (short paper). cAESAR 2020: 7-10Google Scholar
- N. Guarino. 1998. Formal Ontology in Information Systems: Proceedings of the 1st International Conference June 6-8, 1998, Trento, Italy (1st. ed.). IOS Press, NLD.Google ScholarDigital Library
- Horvitz, E., Breese, J., Heckerman, D., Hovel, D. and Rommelse, D. (1998) ‘The Lurniere Project: Bayesian user modelling for inferring the goals and needs of software users’, Proceedings of the 14th Conf. on Uncertainty in Artificial Intelligence, Madison, WI, pp.256–265.Google Scholar
- Anthony Jameson, Silvia Gabrielli, Per Ola Kristensson, Katharina Reinecke, Federica Cena, Cristina Gena, and Fabiana Vernero. 2011. How can we support users' preferential choice? In CHI '11 Extended Abstracts on Human Factors in Computing Systems (CHI EA '11). Association for Computing Machinery, New York, NY, USA, 409–418. https://doi.org/10.1145/1979742.1979620Google ScholarDigital Library
- Dominik Heckmann, Tim Schwartz, Boris Brandherm, Michael Schmitz, Margeritta von Wilamowitz-Moellendorff: Gumo - The General User Model Ontology. User Modeling 2005: 428-432Google Scholar
- Lieberman, H. (1995) ‘Letizia: an agent that assists web browsing’, Proceedings of the Int. Joint Conf. on Artificial Intelligence, Montreal, Canada, pp.924–929.Google Scholar
- Mabbott, A. and Bull, S. (2004) ‘Alternative views on knowledge: presentation of open learner models’, Proceedings of the 7th Int. Conf. on Intelligent Tutoring Systems, Maceiò, Alagoas, Brazil, pp.689–698.Google Scholar
- Micarelli, A., Sciarrone, F. Anatomy and Empirical Evaluation of an Adaptive Web-Based Information Filtering System. User Model User-Adap Inter 14, 159–200 (2004). https://doi.org/10.1023/B:USER.0000028981.43614.94Google ScholarDigital Library
- Pazzani, M.J. and Billsus, D. (2007) ‘Content-based recommendation systems’, The Adaptive Web: Methods and Strategies of Web Personalization, Springer-Verlag, Heidelberg, Germany.Google Scholar
- Pennisi P, Tonacci A, Tartarisco G, Billeci L, Ruta L, Gangemi S, Pioggia G. Autism and social robotics: A systematic review. Autism Res. 2016 Feb;9(2):165-83. doi: 10.1002/aur.1527. Epub 2015 Oct 20. PMID: 26483270.Google Scholar
- Brian Scassellati, Henny Admoni, and Maja Matarić, Robots for Use in Autism Research, Annual Review of Biomedical Engineering 2012 14:1, 275-294Google Scholar
- Sergey Sosnovsky and Darina Dicheva. 2010. Ontological technologies for user modelling. Int. J. Metadata Semant. Ontologies 5, 1 (April 2010), 32–71. https://doi.org/10.1504/IJMSO.2010.032649Google ScholarDigital Library
- Mazzei, L. Anselma, F. D. Michieli, A. Bolioli, M. Casu, J. Gerbrandy, and I. Lunardi. Mobile computing and artificial intelligence for diet management. In New Trends in Image Analysis and Processing - ICIAP 2015 Workshops - ICIAP 2015 International Workshops: BioFor, CTMR, RHEUMA, ISCA, MADiMa, SBMI, and QoEM, Genoa, Italy, September 7-8, 2015, Proceedings, number 9281 in Lecture Notes in Computer Science, pages 342–349. Springer, September 2015. ISBN 978-3-319-23221-8.Google Scholar
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