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Environmental Sounds Classification Based on Visual Features

  • Sameh Souli
  • Zied Lachiri
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7042)

Abstract

This paper presents a method aimed at classification of the environmental sounds in the visual domain by using the scale and translation invariance. We present a new approach that extracts visual features from sound spectrograms. We suggest to apply support vector machines (SVM’s) in order to address sound classification. Indeed, in the proposed method we explore sound spectrograms as texture images, and extracts the time-frequency structures by using a translation-invariant wavelet transform and a patch transform alternated with local maximum and global maximum to pursuit scale and translation invariance. We illustrate the performance of this method on an audio database, which composed of 10 sounds classes. The obtained recognition rate is of the order 91.82 % with the multiclass decomposition method: One-Against-One.

Keywords

Environmental sounds Visual features Translation-invariant wavelet transform Spectrogram SVM Multiclass 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Sameh Souli
    • 1
  • Zied Lachiri
    • 1
    • 2
  1. 1.Signal, Image and pattern recognition research unit Dept. of Genie ElectriqueENITLe BelvédèreTunisia
  2. 2.Dept. of Physique and InstrumentationINSATCentre UrbainTunisia

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