• DocumentCode
    1857401
  • Title

    A system for machine recognition of music patterns

  • Author

    Coyle, Edward J. ; Shmulevich, Ilya

  • Author_Institution
    Electr. & Comput. Eng., Purdue Univ., West Lafayette, IN, USA
  • Volume
    6
  • fYear
    1998
  • fDate
    12-15 May 1998
  • Firstpage
    3597
  • Abstract
    We introduce a system for machine recognition of music patterns. The problem is put into a pattern recognition framework in the sense that an error between a target pattern and scanned pattern is minimized. The error takes into account pitch and rhythm information. The pitch error measure consists of an absolute (objective) error and a perceptual error. The latter depends on an algorithm for establishing the tonal context which is based on Krumhansl´s (1990) key-finding algorithm. The sequence of maximum correlations that it outputs is smoothed with a cubic spline and is used to determine weights for perceptual and absolute pitch errors. Maximum correlations are used to create the assigned key sequence, which is then filtered by a recursive median filter to improve the structure of the output of the key finding algorithm. A procedure for choosing weights given to pitch and rhythm errors is discussed
  • Keywords
    error analysis; interpolation; median filters; music; pattern recognition; recursive filters; signal representation; smoothing methods; splines (mathematics); cubic spline; error minimization; key-finding algorithm; machine recognition; maximum correlation sequence; music patterns; objective error; perceptual error; pitch error measure; pitch representation; recursive median filter; rhythm error; rhythm representation; scanned pattern; target pattern; tonal context; Computer errors; Encoding; Filters; Frequency; Humans; Multiple signal classification; Pattern recognition; Rhythm; Spline; Target recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
  • Conference_Location
    Seattle, WA
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-4428-6
  • Type

    conf

  • DOI
    10.1109/ICASSP.1998.679656
  • Filename
    679656