• DocumentCode
    179237
  • Title

    Temporal synchronization of multiple audio signals

  • Author

    Kammerl, Julius ; Birkbeck, Neil ; Inguva, Sasi ; Kelly, Denis ; Crawford, A.J. ; Denman, Hugh ; Kokaram, Anil ; Pantofaru, C.

  • Author_Institution
    Google, Inc., Mountain View, CA, USA
  • fYear
    2014
  • fDate
    4-9 May 2014
  • Firstpage
    4603
  • Lastpage
    4607
  • Abstract
    Given the proliferation of consumer media recording devices, events often give rise to a large number of recordings. These recordings are taken from different spatial positions and do not have reliable timestamp information. In this paper, we present two robust graph-based approaches for synchronizing multiple audio signals. The graphs are constructed atop the over-determined system resulting from pairwise signal comparison using cross-correlation of audio features. The first approach uses a Minimum Spanning Tree (MST) technique, while the second uses Belief Propagation (BP) to solve the system. Both approaches can provide excellent solutions and robustness to pairwise outliers, however the MST approach is much less complex than BP. In addition, an experimental comparison of audio features-based synchronization shows that spectral flatness outperforms the zero-crossing rate and signal energy.
  • Keywords
    audio recording; audio signal processing; graph theory; multimedia communication; BP; MST technique; audio features; audio features based synchronization; belief propagation; consumer media recording devices; minimum spanning tree; multiple audio signals; pairwise signal comparison; robust graph based approaches; signal energy; spatial positions; temporal synchronization; timestamp information; zero crossing rate; Belief propagation; Correlation; Feature extraction; Multimedia communication; Robustness; Streaming media; Synchronization; Multi-signal synchronization; audio feature analysis; belief propagation; minimum spanning tree;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
  • Conference_Location
    Florence
  • Type

    conf

  • DOI
    10.1109/ICASSP.2014.6854474
  • Filename
    6854474