• DocumentCode
    2151142
  • Title

    Time domain reconstruction of spatial sound fields using compressed sensing

  • Author

    Wabnitz, Andrew ; Epain, Nicolas ; Van Schaik, André ; Jin, Craig

  • Author_Institution
    Comput. & Audio Res. Lab. (CARLab), Univ. of Sydney, Sydney, NSW, Australia
  • fYear
    2011
  • fDate
    22-27 May 2011
  • Firstpage
    465
  • Lastpage
    468
  • Abstract
    A novel technique for time domain spatial sound reproduction using compressed sensing is presented. The presented technique is based on the application of compressed sensing theory, which is used to improve the accuracy of the reconstructed sound field. In addition, singular value decomposition is also applied, which acts to significantly reduce the size of the data set to process, thus making it efficient and realisable for real-time applications. Results are presented from the preliminary performance evaluation of the compressed sensing technique in comparison to the Higher Order Ambisonic reconstruction technique.
  • Keywords
    acoustic signal processing; signal reconstruction; singular value decomposition; time-domain analysis; compressed sensing; data set; higher order ambisonic reconstruction technique; performance evaluation; singular value decomposition; time domain sound field reconstruction; time domain spatial sound field reproduction; Arrays; Compressed sensing; Harmonic analysis; Image reconstruction; Loudspeakers; Optimization; Receivers; Acoustic signal processing; Optimization; Signal reconstruction; Sparse matrices;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
  • Conference_Location
    Prague
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4577-0538-0
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2011.5946441
  • Filename
    5946441