• DocumentCode
    1330969
  • Title

    Sparse Representations in Audio and Music: From Coding to Source Separation

  • Author

    Plumbley, Mark D. ; Blumensath, Thomas ; Daudet, Laurent ; Gribonval, Rémi ; Davies, Mike E.

  • Author_Institution
    Sch. of Electron. Eng. & Comput. Sci., Queen Mary Univ. of London, London, UK
  • Volume
    98
  • Issue
    6
  • fYear
    2010
  • fDate
    6/1/2010 12:00:00 AM
  • Firstpage
    995
  • Lastpage
    1005
  • Abstract
    Sparse representations have proved a powerful tool in the analysis and processing of audio signals and already lie at the heart of popular coding standards such as MP3 and Dolby AAC. In this paper we give an overview of a number of current and emerging applications of sparse representations in areas from audio coding, audio enhancement and music transcription to blind source separation solutions that can solve the ??cocktail party problem.?? In each case we will show how the prior assumption that the audio signals are approximately sparse in some time-frequency representation allows us to address the associated signal processing task.
  • Keywords
    Fourier transforms; audio coding; blind source separation; audio coding; blind source separation; signal processing; sparse representations; Audio coding; Councils; Discrete Fourier transforms; Discrete wavelet transforms; Fourier transforms; Multiple signal classification; Resonance; Signal analysis; Signal processing; Source separation; Audio coding; Fourier transforms; basis functions; discrete cosine transforms; music; signal representations; wavelet transforms;
  • fLanguage
    English
  • Journal_Title
    Proceedings of the IEEE
  • Publisher
    ieee
  • ISSN
    0018-9219
  • Type

    jour

  • DOI
    10.1109/JPROC.2009.2030345
  • Filename
    5332363