• DocumentCode
    2330360
  • Title

    Spoken command of large mobile robots in outdoor environments

  • Author

    Chuangsuwanich, Ekapol ; Cyphers, Scott ; Glass, James ; Teller, Seth

  • Author_Institution
    MIT Comput. Sci. & Artificial Intell. Lab., Cambridge, MA, USA
  • fYear
    2010
  • fDate
    12-15 Dec. 2010
  • Firstpage
    306
  • Lastpage
    311
  • Abstract
    We describe a speech system for commanding robots in human-occupied outdoor military supply depots. To operate in such environments, the robots must be as easy to interact with as are humans, i.e. they must reliably understand ordinary spoken instructions, such as orders to move supplies, as well as commands and warnings, spoken or shouted from distances of tens of meters. These design goals preclude close-talking microphones and “push-to-talk” buttons that are typically used to isolate commands from the sounds of vehicles, machinery and non-relevant speech. We used multiple microphones to provide omnidirectional coverage. A novel voice activity detector was developed to detect speech and select the appropriate microphone to listen to. Finally, we developed a recognizer model that could successfully recognize commands when heard amidst other speech within a noisy environment. When evaluated on speech data in the field, this system performed significantly better than a more computationally intensive baseline system, reducing the effective false alarm rate by a factor of 40, while maintaining the same level of precision.
  • Keywords
    human-robot interaction; microphones; mobile robots; speech recognition; close talking microphones; human occupied outdoor military supply depots; large mobile robots; push-to-talk buttons; speech detection; spoken command; voice activity detector; Human-robot interaction; modulation frequency; real-time speech recognition; voice activity detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Spoken Language Technology Workshop (SLT), 2010 IEEE
  • Conference_Location
    Berkeley, CA
  • Print_ISBN
    978-1-4244-7904-7
  • Electronic_ISBN
    978-1-4244-7902-3
  • Type

    conf

  • DOI
    10.1109/SLT.2010.5700869
  • Filename
    5700869