• DocumentCode
    1558342
  • Title

    Structural Segmentation of Multitrack Audio

  • Author

    Hargreaves, Steven ; Klapuri, Anssi ; Sandler, Mark

  • Author_Institution
    Centre for Digital Music, Department of Electronic Engineering, Queen Mary University of London, London, UK
  • Volume
    20
  • Issue
    10
  • fYear
    2012
  • Firstpage
    2637
  • Lastpage
    2647
  • Abstract
    Structural segmentation of musical audio signals is one of many active areas of Music Information Retrieval (MIR) research. One aspect of this important topic which has so far received little attention though is the potential advantage to be gained by utilizing multitrack audio. This paper gives an overview of current segmentation techniques, and demonstrates that by applying a particular segmentation algorithm to multitrack data, rather than the usual case of fully mixed audio, we achieve a significant and quantifiable increase in accuracy when locating segment boundaries. Additionally, we provide details of a structurally annotated multitrack test set available for use by other researchers.
  • Keywords
    Feature extraction; Indexes; Music information retrieval; Signal processing algorithms; Timbre; Audio; multitrack; music information retrieval (MIR); structural segmentation;
  • fLanguage
    English
  • Journal_Title
    Audio, Speech, and Language Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1558-7916
  • Type

    jour

  • DOI
    10.1109/TASL.2012.2209419
  • Filename
    6243190