Homonymy Resolution During Interpretation of Speech Commands by a Mobile Robot

Мұқаба

Дәйексөз келтіру

Толық мәтін

Аннотация

Modern companion robots can solve a wide range of tasks while working together with a person. During the collaboration, a robot can receive commands from a person through various control systems, as well as use natural language. Utterances in natural language have significant degree of ambiguity (homonymy). In this paper we examine the methods, used to process utterances, and solve the possible homonymy during speech control of a robot in a natural or virtual environment.

Толық мәтін

Рұқсат жабық

Авторлар туралы

Artemy Kotov

Kurchatov Institute; Russian State University for the Humanities; Moscow State Linguistic University

Хат алмасуға жауапты Автор.
Email: kotov@harpia.ru

Candidate of Philological Sciences, Leading Researcher; Researcher; Leading Researcher

Ресей, Moscow; Moscow; Moscow

Nikita Arinkin

Kurchatov Institute; Russian State University for the Humanities

Email: arinkin_na@nrcki.ru

Researcher; Researcher

Ресей, Moscow; Moscow

Ludmila Zaidelman

Kurchatov Institute; Russian State University for the Humanities

Email: zaydelman_ly@nrcki.ru

Researcher; Researcher

Ресей, Moscow; Moscow

Anna Zinina

Kurchatov Institute; Russian State University for the Humanities; Moscow State Linguistic University

Email: zinina_aa@nrcki.ru

Candidate of Psychological Sciences, Researcher; Researcher; Leading Researcher

Ресей, Moscow; Moscow; Moscow

Maxim Rovbo

Kurchatov Institute

Email: rovboma@gmail.com

Researcher

Ресей, Moscow

Petr Sorokoumov

Kurchatov Institute

Email: petr.sorokoumov@gmail.com

Researcher

Ресей, Moscow

Alexander Filatov

Russian State University for the Humanities

Email: filatov.alex@gmail.com

Analyst

Ресей, Moscow

Әдебиет тізімі

  1. Winograd, T., and F. Flores. 1987. Understanding Computers and Cognition: A New Foundation for Design. Addison-Wesley. 224 p.
  2. Winograd, T. 1972. Understanding Natural Language. Cognitive Psychology 3(1):1–191.
  3. Breazeal, C., A. Takanishi, and T. Kobayashi. 2008. Social Robots That Interact with People BT Springer Handbook of Robotics. Berlin, Heidelberg: Springer Berlin Heidelberg. 1349–69.
  4. Gladky, A. V. 1985. Sintaksicheskie struktury estestvennogo yazyka v avtomatizirovannyh sistemah obshcheniya [Syntactic Structures of Natural Language for Automation System of Discourse]. Moscow: Nauka.
  5. Austin, J. 1962. How To Do Things with Words. Oxford. Clarendon Press.
  6. Searle, J. R. 1976. A classification of illocutionary acts. Language in society. Vol. 5. №. 1. P. 1-23.
  7. Vanzo, A., D. Croce, E. Bastianelli, R. Basili, and D. Nardi. 2020. Grounded Language Interpretation of Robotic Commands through Structured Learning. Artificial Intelligence. 278:103181.
  8. Marge, M., C. Espy-Wilson, N. G. Ward, A. Alwan, Y. Artzi, M. Bansal, G. Blankenship, J. Chai, H. Daumé, D. Dey, M. Harper, T. Howard, C. Kennington, I. KruijffKorbayová, D. Manocha, C. Matuszek, R. Mead, R. Mooney, R. K. Moore, M. Ostendorf, H. Pon-Barry, A. I. Rudnicky, M. Scheutz, R. St Amant, T. Sun, S. Tellex, D. Traum, and Z. Yu. 2021. Spoken Language Interaction with Robots: Recommendations for Future Research. Computer Speech and Language 71(July 2021):101255.
  9. Mukherjee, D., K. Gupta, L. H. Chang, and H. Najjaran. 2022. A Survey of Robot Learning Strategies for HumanRobot Collaboration in Industrial Settings. Robotics and Computer-Integrated Manufacturing 73(October 2020):102231.
  10. Karpov, V. E., D. G. Malakhov, A. D. Moscowsky, M. A. Rovbo, P. S. Sorokoumov, B. M. Velichkovsky, and V. L. Ushakov. 2019. Architecture of a Wheelchair Control System for Disabled People: Towards Multifunctional Robotic Solution with Neurobiological Interfaces. Sovremennye Tehnologii v Medicine 11(1):90–102.
  11. Fillmore, C. J. 1968. The Case for Case. Universals in linguistic theory, edited by E. Bach and R. T. Harms. New York: Holt, Rinehart & Winston. P. 1–68.
  12. Baker, C. F., C. J. Fillmore, and J. B. Lowe. 1998. The Berkeley FrameNet Project.
  13. Paducheva, E.V. 2001. Vyskazyvanie i ego sootnesennost' s deistvitel'nost'yu [Utterance and its relations with reality]. Editorial URSS.
  14. Brown, P., and S. C. Levinson. 1987. Politeness: Some Universals in Language Usage (Studies in Interactional Sociolinguistics). Cambridge.
  15. Rosch, E., C. B. Mervis, W. D. Gray, D. M. Johnson, and P. Boyes-Braem. 1976. Basic Objects in Natural Categories. Cognitive Psychology 8(3):382–439.
  16. Paducheva, E. V. 2019. Egotsentricheskiye yedinitsy yazyka [Egocentric units of language]. Publishing house YASK.
  17. Osipov, G. S., N. V. Chudova, A. I. Panov, and Yu. M. Kuznetsova. 2018. Znakovaya kartina mira sub”ekta povedeniya [An Iconic Picture of the World of the Subject of Behavior]. Moscow: Fizmatlit.
  18. Abu-Salih, B. 2021. Domain-Specific Knowledge Graphs: A Survey. Journal of Network and Computer Applications 185(April):103076.
  19. Kirrane, S. 2021. Intelligent Software Web Agents: A Gap Analysis. Journal of Web Semantics 71:100659. doi: 10.1016/j.websem. 2021.100659.
  20. W3C. 2014a. RDF 1.1 Concepts and Abstract Syntax. Available at: https://www.w3.org/TR/rdf11concepts/.
  21. Sorokoumov, P. S., M. A. Rovbo, A. D. Moscowsky, and A. Malyshev. 2021. Robotic Wheelchair Control System for Multimodal Interfaces Based on a Symbolic Model of the World. Smart Electromechanical Systems. P. 163–83.
  22. Brickley, Dan, and R. V. Guha. 2014. RDF Schema 1.1.
  23. W3C. 2014c. RDF 1.1 Primer. Available at: https://www.w3.org/TR/rdf11-primer/.
  24. W3C. 2014d. RDF Schema 1.1. Available at: https://www.w3.org/TR/rdf-schema/.
  25. W3C. 2014b. RDF 1.1 N-Triples. Available at: https://www.w3.org/TR/2014/REC-n-triples-20140225/.
  26. Buchanan, B. G. 1984. Rule Based Expert Systems: The Mycin Experiments of the Stanford Heuristic Programming Project. 1st ed. edited by E. H. Shortliffe. The Addison-Wesley series in artificial intelligence.
  27. Rovbo, M. A., and P. S. Sorokoumov. 2022. Symbolic Control System for a Mobile Robotic Platform Based on Soar Cognitive Architecture. Smart Electromechanical Systems. P. 259–75.
  28. Rovbo, M. A., and P. S. Sorokoumov. 2021. Znakovaya sistema upravleniya mobil'noj platformoj [Iconic Mobile Platform Management System]. Programmnye Produkty i Sistemy 4(34):543–54.

Қосымша файлдар

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Әрекет
1. JATS XML
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2. Fig. 1. Software architecture of the main robot control loop

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3. Fig. 2. Software architecture of the speech interface

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4. Fig. 3. Semantic network of RDF representation of parsing the phrase ‘drive to the house on the left of the forest’

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5. Fig. 4. Examples of systems using robot speech interface: remotely controlled platform in a virtual environment (left), robotic wheelchair (right)

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