• DocumentCode
    2535478
  • Title

    Strategies for orca call retrieval to support collaborative annotation of a large archive

  • Author

    Ness, Steven R. ; Lerch, Alex ; Tzanetakis, George

  • Author_Institution
    Comput. Sci., Univ. of Victoria, Victoria, BC, Canada
  • fYear
    2011
  • fDate
    17-19 Oct. 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The Orchive is a large audio archive of hydrophone recordings of Killer whale (Orcinus orca) vocalizations. Researchers and users from around the world can interact with the archive using a collaborative web-based annotation, visualization and retrieval interface. In addition a mobile client has been written in order to crowdsource Orca call annotation. In this paper we describe and compare different strategies for the retrieval of discrete Orca calls. In addition, the results of the automatic analysis are integrated in the user interface facilitating annotation as well as leveraging the existing annotations for supervised learning. The best strategy achieves a mean average precision of 0.77 with the first retrieved item being relevant 95% of the time in a dataset of 185 calls belonging to 4 types.
  • Keywords
    audio signal processing; hydrophones; information retrieval; learning (artificial intelligence); user interfaces; Killer whale vocalizations; audio archive; collaborative Web-based annotation; collaborative annotation; crowdsource Orca call annotation; hydrophone recordings; mobile client; orca call retrieval; retrieval interface; supervised learning; user interface; Collaboration; Correlation; Games; Mobile communication; Noise measurement; Sonar equipment; Whales;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Signal Processing (MMSP), 2011 IEEE 13th International Workshop on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4577-1432-0
  • Electronic_ISBN
    978-1-4577-1433-7
  • Type

    conf

  • DOI
    10.1109/MMSP.2011.6093798
  • Filename
    6093798