• DocumentCode
    3845732
  • Title

    Three Dimensions of Pitched Instrument Onset Detection

  • Author

    André Holzapfel;Yannis Stylianou;Ali C. Gedik;Barış Bozkurt

  • Author_Institution
    Institute of Computer Science, FORTH, Greece
  • Volume
    18
  • Issue
    6
  • fYear
    2010
  • Firstpage
    1517
  • Lastpage
    1527
  • Abstract
    In this paper, we suggest a novel group delay based method for the onset detection of pitched instruments. It is proposed to approach the problem of onset detection by examining three dimensions separately: phase (i.e., group delay), magnitude and pitch. The evaluation of the suggested onset detectors for phase, pitch and magnitude is performed using a new publicly available and fully onset annotated database of monophonic recordings which is balanced in terms of included instruments and onset samples per instrument, while it contains different performance styles. Results show that the accuracy of onset detection depends on the type of instruments as well as on the style of performance. Combining the information contained in the three dimensions by means of a fusion at decision level leads to an improvement of onset detection by about 8% in terms of F-measure, compared to the best single dimension.
  • Keywords
    "Instruments","Signal processing algorithms","Delay","Signal processing","Phase detection","Event detection","Robustness","Computer science","Detectors","Performance evaluation"
  • Journal_Title
    IEEE Transactions on Audio, Speech, and Language Processing
  • Publisher
    ieee
  • ISSN
    1558-7916
  • Type

    jour

  • DOI
    10.1109/TASL.2009.2036298
  • Filename
    5337997