• DocumentCode
    667552
  • Title

    About this non-negative business

  • Author

    Smaragdis, Paris

  • Author_Institution
    Univ. of Illinois, Urbana, IL, USA
  • fYear
    2013
  • fDate
    20-23 Oct. 2013
  • Firstpage
    1
  • Lastpage
    1
  • Abstract
    Summary form only given: The foundations of signal processing are firmly set in least squares, an approach that has served us very well for years (and still does). With the increasing presence of machine learning and sophisticated statistics in audio processing, we are slowly seeing that not everything has to be based on Gaussians anymore. One recently popular approach along these lines is that of non-negative modeling, especially in problems that involve complex audio mixtures. In this keynote I´ll talk about how these models came to be, what they can do, why they have been so successful, and I´ll ponder on what the future holds as new developments are continuously coming in.
  • Keywords
    audio signal processing; learning (artificial intelligence); least squares approximations; audio processing; complex audio mixtures; least squares; machine learning; nonnegative modeling; signal processing; Acoustics; Business; Committees; Computer science; Conferences; Educational institutions; Signal processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applications of Signal Processing to Audio and Acoustics (WASPAA), 2013 IEEE Workshop on
  • Conference_Location
    New Paltz, NY
  • ISSN
    1931-1168
  • Type

    conf

  • DOI
    10.1109/WASPAA.2013.6701898
  • Filename
    6701898