• DocumentCode
    1764486
  • Title

    Melody Extraction from Polyphonic Music Signals: Approaches, applications, and challenges

  • Author

    Salamon, Justin ; Gomez, Eva ; Ellis, Daniel P. W. ; Richard, Guilhem

  • Author_Institution
    Dept. of Inf. &Commun. Technol., Univ. Pompeu Fabra, Barcelona, Spain
  • Volume
    31
  • Issue
    2
  • fYear
    2014
  • fDate
    41699
  • Firstpage
    118
  • Lastpage
    134
  • Abstract
    Melody extraction algorithms aim to produce a sequence of frequency values corresponding to the pitch of the dominant melody from a musical recording. Over the past decade, melody extraction has emerged as an active research topic, comprising a large variety of proposed algorithms spanning a wide range of techniques. This article provides an overview of these techniques, the applications for which melody extraction is useful, and the challenges that remain. We start with a discussion of ?melody? from both musical and signal processing perspectives and provide a case study that interprets the output of a melody extraction algorithm for specific excerpts. We then provide a comprehensive comparative analysis of melody extraction algorithms based on the results of an international evaluation campaign. We discuss issues of algorithm design, evaluation, and applications that build upon melody extraction. Finally, we discuss some of the remaining challenges in melody extraction research in terms of algorithmic performance, development, and evaluation methodology.
  • Keywords
    audio signal processing; information retrieval; music; algorithm design; algorithm evaluation; audio signal processing; dominant melody pitch; frequency value sequence; international evaluation campaign; melody extraction algorithms; music information retrieval; musical processing perspectives; musical recording; polyphonic music signals; Data mining; Harmonic analysis; Instruments; Multiple signal classification; Music; Signal processing algorithms; Time-frequency analysis;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/MSP.2013.2271648
  • Filename
    6739213