• DocumentCode
    2171796
  • Title

    Optimal cost function and magnitude power for NMF-based speech separation and music interpolation

  • Author

    King, Brian ; Févotte, Cédric ; Smaragdis, Paris

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Washington, Seattle, WA, USA
  • fYear
    2012
  • fDate
    23-26 Sept. 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    There has been a significant amount of research in new algorithms and applications for nonnegative matrix factorization, but relatively little has been published on practical considerations for real-world applications, such as choosing optimal parameters for a particular application. In this paper, we will look at two applications, single-channel source separation of speech and interpolating missing music data. We will present the optimal parameters found for the experiments as well as discuss how parameters affect performance.
  • Keywords
    interpolation; matrix decomposition; music; speech processing; NMF-based speech separation; magnitude power; missing music data; music interpolation; nonnegative matrix factorization; optimal cost function; single-channel source separation; Cost function; Interpolation; Source separation; Speech; Training data; Tunneling magnetoresistance; Vectors; Nonnegative matrix factorization; source separation; spectrogram interpolation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning for Signal Processing (MLSP), 2012 IEEE International Workshop on
  • Conference_Location
    Santander
  • ISSN
    1551-2541
  • Print_ISBN
    978-1-4673-1024-6
  • Electronic_ISBN
    1551-2541
  • Type

    conf

  • DOI
    10.1109/MLSP.2012.6349726
  • Filename
    6349726