• DocumentCode
    1822426
  • Title

    Low-Traffic and Low-Power Data-Intensive Sound Acquisition with Perfect Aggregation Specialized for Microphone Array Networks

  • Author

    Noguchi, Hiroki ; Takagi, Tomoya ; Kugata, Koji ; Yoshimoto, Masahiko ; Kawaguchi, Hiroshi

  • Author_Institution
    Dept. of Comput. & Syst. Eng., Kobe Univ., Kobe, Japan
  • fYear
    2010
  • fDate
    18-25 July 2010
  • Firstpage
    157
  • Lastpage
    162
  • Abstract
    We propose a microphone array network that realizes ubiquitous sound acquisition. Several nodes with 16 microphones are connected to form a novel huge sound acquisition system, which carries out voice activity detection (VAD), sound source localization, and separation. The three operations are distributed among nodes. Using the distributed network, we achieve a low-traffic data-intensive array network. To manage nodes´ power consumption, VAD is implemented. Consequently, the system uses little power when speech is not active. For sound localization, a network-connected multiple signal classification (MUSIC) algorithm is used. The sound separation system can improve a signal-noise ratio (SNR) by 7.75 dB using 112 microphones. Network traffic is reduced by 99.11% when using 1024 microphones.
  • Keywords
    acoustic signal detection; microphone arrays; signal classification; MUSIC algorithm; SNR; VAD; data intensive sound acquisition system; distributed network; microphone array networks; network traffic; network-connected multiple signal classification algorithm; nodes power consumption; signal-noise ratio; sound source localization; sound source separation; voice activity detection; Accuracy; Arrays; Microphones; Multiple signal classification; Signal to noise ratio; Speech; Synchronization; low-power system; microphone array; perfect aggregation; sensor network; ubiquitous sensing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Sensor Technologies and Applications (SENSORCOMM), 2010 Fourth International Conference on
  • Conference_Location
    Venice
  • Print_ISBN
    978-1-4244-7538-4
  • Type

    conf

  • DOI
    10.1109/SENSORCOMM.2010.32
  • Filename
    5558069