Repeating Pattern Discovery from Audio Stream

  • Zhen-Long Du
  • Xiao-Li Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3930)


In this paper, an effective method to discover repeating pattern from audio is proposed. Since the previous feature extraction methods are usually process monophony audio, for extracting more descriptive features from polyphony audio, Gabor filters bank is introduced. Meanwhile the measure criteria is suggested for qualitatively and quantitatively weighting the discernibility of extracted features. In addition, the presented algorithm is based on the incremental match and has time complexity O(nlog(n)). Experimental evaluations show that our proposed method could extract complete and meaningful repeating patterns from polyphony audio.


Gabor Filter Short Time Fourier Transform Audio Feature Audio Stream Indexing Accuracy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Zhen-Long Du
    • 1
    • 2
  • Xiao-Li Li
    • 1
  1. 1.Lanzhou University of TechnologyLanzhouP.R. China
  2. 2.State Key Lab of CAD&CGZhejiang UniversityHangzhouP.R. China

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