• DocumentCode
    900456
  • Title

    Automated classification of piano-guitar notes

  • Author

    Fragoulis, Dimitrios ; Papaodysseus, Constantin ; Exarhos, Mihalis ; Roussopoulos, George ; Panagopoulos, Thanasis ; Kamarotos, Dimitrios

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens, Greece
  • Volume
    14
  • Issue
    3
  • fYear
    2006
  • fDate
    5/1/2006 12:00:00 AM
  • Firstpage
    1040
  • Lastpage
    1050
  • Abstract
    In this paper, a new decisively important factor in both the perceptual and the automated piano-guitar identification process is introduced. This factor is determined by the nontonal spectral content of a note, while it is, in practice, totally independent of the note spectrum tonal part. This conclusion and all related results are based on a number of extended acoustical experiments, performed over the full pitch range of each instrument. The notes have been recorded from six different performers each of whom played a different instrument. Next, a number of powerful criteria for the classification between guitar and piano is proposed. Using these criteria, automated classification between 754 piano and guitar test notes has been achieved with a 100% success rate.
  • Keywords
    acoustic signal processing; musical instruments; signal classification; automated piano-guitar identification; nontonal spectral content; piano-guitar notes classification; Automatic testing; Helium; Instruments; Multidimensional systems; Music; Neural networks; Power engineering and energy; Speech; Steady-state; Timbre; Musical instrument classification; noontonal spectrum; timbre identification; timbre recognition;
  • fLanguage
    English
  • Journal_Title
    Audio, Speech, and Language Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1558-7916
  • Type

    jour

  • DOI
    10.1109/TSA.2005.857571
  • Filename
    1621216