Spoken Language Understanding for Service Robotics in Italian

  • Andrea Vanzo
  • Danilo Croce
  • Giuseppe Castellucci
  • Roberto Basili
  • Daniele Nardi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10037)


Robots operate in specific environments and the correct interpretation of linguistic interactions depends on physical, cognitive and language-dependent aspects triggered by the environment. In this work, we describe a Spoken Language Understanding chain for the semantic parsing of robotic commands, designed according to a Client/Server architecture. This work also reports a first evaluation of the proposed architecture in the automatic interpretation of commands expressed in Italian for a robot in a Service Robotics domain. The experimental results show that the proposed solution can be easily extended to other languages for a robust Spoken Language Understanding in Human-Robot Interaction.


Spoken language understanding Automatic interpretation of robotic commands Grounded language learning Human robot interaction 


  1. 1.
    Harnad, S.: The symbol grounding problem. Physica D Nonlinear Phenom. 42(1–3), 335–346 (1990)CrossRefGoogle Scholar
  2. 2.
    Tanenhaus, M., Spivey-Knowlton, M., Eberhard, K., Sedivy, J.: Integration of visual and linguistic information during spoken language comprehension. Science 268, 1632–1634 (1995)CrossRefGoogle Scholar
  3. 3.
    Nüchter, A., Hertzberg, J.: Towards semantic maps for mobile robots. Robot. Auton. Syst. 56(11), 915–926 (2008)CrossRefGoogle Scholar
  4. 4.
    Diosi, A., Taylor, G.R., Kleeman, L.: Interactive SLAM using laser and advanced sonar. In: Proceedings of the 2005 International Conference on Robotics and Automation, pp. 1103–1108 (2005)Google Scholar
  5. 5.
    Chen, D.L., Mooney, R.J.: Learning to interpret natural language navigation instructions from observations. In: Proceedings of the 25th AAAI Conference, pp. 859–865 (2011)Google Scholar
  6. 6.
    Matuszek, C., Herbst, E., Zettlemoyer, L.S., Fox, D.: Learning to parse natural language commands to a robot control system. In: Desai, J.P., Dudek, G., Khatib, O., Kumar, V. (eds.) Experimental Robotics. STAR, vol. 88, pp. 403–415. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  7. 7.
    Bastianelli, E., Castellucci, G., Croce, D., Basili, R., Nardi, D.: Effective and robust natural language understanding for human-robot interaction. In: Proceedings of ECAI 2014. IOS Press (2014)Google Scholar
  8. 8.
    Tellex, S., Kollar, T., Dickerson, S., Walter, M., Banerjee, A., Teller, S., Roy, N.: Approaching the symbol grounding problem with probabilistic graphical models. AI Mag. 32(4), 64 (2011)Google Scholar
  9. 9.
    Matuszek, C., FitzGerald, N., Zettlemoyer, L.S., Bo, L., Fox, D.: A joint model of language and perception for grounded attribute learning. In: ICML. (2012)Google Scholar
  10. 10.
    Bastianelli, E., Croce, D., Vanzo, A., Basili, R., Nardi, D.: A discriminative approach to grounded spoken language understanding in interactive robotics. In: Proceedings of the 25th IJCAI, New York (2016)Google Scholar
  11. 11.
    Fillmore, C.J.: Frames and the semantics of understanding. Quad. Semantica 6(2), 222–254 (1985)Google Scholar
  12. 12.
    Baker, C.F., Fillmore, C.J., Lowe, J.B.: The berkeley framenet project. In: Proceedings of ACL and COLING, pp. 86–90 (1998)Google Scholar
  13. 13.
    Basili, R., Zanzotto, F.M.: Parsing engineering and empirical robustness. Nat. Lang. Eng. 8(3), 97–120 (2002)Google Scholar
  14. 14.
    Basili, R., Bastianelli, E., Castellucci, G., Nardi, D., Perera, V.: Kernel-based discriminative re-ranking for spoken command understanding in HRI. In: Baldoni, M., Baroglio, C., Boella, G., Micalizio, R. (eds.) AI*IA 2013. LNCS (LNAI), vol. 8249, pp. 169–180. Springer, Heidelberg (2013). doi: 10.1007/978-3-319-03524-6_15 CrossRefGoogle Scholar
  15. 15.
    Altun, Y., Tsochantaridis, I., Hofmann, T.: Hidden markov support vector machines. In: Proceedings of ICML (2003)Google Scholar
  16. 16.
    Banarescu, L., Bonial, C., Cai, S., Georgescu, M., Griffitt, K., Hermjakob, U., Knight, K., Koehn, P., Palmer, M., Schneider, N.: Abstract meaning representation for sembanking. In: Proceedings of the 7th Linguistic Annotation Workshop and Interoperability with Discourse, Sofia, Bulgaria, ACL, pp. 178–186, August 2013Google Scholar
  17. 17.
    Bastianelli, E., Castellucci, G., Croce, D., Basili, R., Nardi, D.: HuRIC: a human robot interaction corpus. In: Proceedings of LREC 2014, Reykjavik, Iceland, May 2014Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Andrea Vanzo
    • 1
  • Danilo Croce
    • 2
  • Giuseppe Castellucci
    • 3
  • Roberto Basili
    • 2
  • Daniele Nardi
    • 1
  1. 1.Department of Computer, Control and Management Engineering “Antonio Ruberti”Sapienza University of RomeRomeItaly
  2. 2.Department of Enterprise EngineeringUniversity of Roma Tor VergataRomeItaly
  3. 3.Department of Electronic EngineeringUniversity of Roma Tor VergataRomeItaly

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