• DocumentCode
    3019332
  • Title

    Associative processes between behavioral symbols and a large scale language model

  • Author

    Takano, Wataru ; Nakamura, Yoshihiko

  • Author_Institution
    Mechano-Inf., Univ. of Tokyo, Tokyo, Japan
  • fYear
    2010
  • fDate
    3-7 May 2010
  • Firstpage
    2404
  • Lastpage
    2409
  • Abstract
    This paper describes an novel approach towards linguistic processing for robots through integration of a motion language model and a natural language model. The motion language model works for association of words from motion symbols. The natural language model is one used for a morphological analysis, which has been developed in natural language community. The natural language model is optimized using a enormous amount of words. So this model is scalable architecture. The motion language model and the natural language model can be integrated since both models are represented graphically. The integration of the motion language model and the natural language model allows robots not only to interpret motion patterns as sentences but also to generate motions from sentences. This paper demonstrates the validity of our proposed framework even in the case that large-scale word corpus is needed processing through experiments of interpreting motion patterns as sentences and generating motion patterns from sentences.
  • Keywords
    natural language processing; robots; associative process; behavioral symbols; large scale language model; large-scale word corpus; linguistic processing; morphological analysis; motion language model; natural language model; robots; Feature extraction; Hidden Markov models; Humanoid robots; Intelligent robots; Large-scale systems; Natural language processing; Natural languages; Robotics and automation; Stochastic processes; USA Councils;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation (ICRA), 2010 IEEE International Conference on
  • Conference_Location
    Anchorage, AK
  • ISSN
    1050-4729
  • Print_ISBN
    978-1-4244-5038-1
  • Electronic_ISBN
    1050-4729
  • Type

    conf

  • DOI
    10.1109/ROBOT.2010.5509532
  • Filename
    5509532