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International Symposium on Computer Music Multidisciplinary Research

CMMR 2013: Sound, Music, and Motion pp 443–462Cite as

Sparse Gabor Multiplier Estimation for Identification of Sound Objects in Texture Sound

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8905))

Abstract

In this contribution we present a novel method for identifying novelty and, more specifically, sound objects within texture sounds. We introduce the notion of texture sound and sound object and explain how the properties of a sound that is known to be textural may be exploited in order to detect deviations which suggest the presence of novelty or distinct sound event, which may then be called sound object. The suggested approach is based on Gabor multipliers, which map the Gabor coefficients corresponding to certain time-segments of the signal to each other. We present the results of simulations based on both synthetic and real audio signals.

This research was supported by the Vienna Science and Technology Fund (WWTF) through project VRG12-009 and the Austrian Science Fund (FWF):[V 312-N25].

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Notes

  1. 1.

    \(\langle g,h\rangle _{L^2}\) denotes the \(L^2\)-inner product, defined as \(\langle g,h\rangle _{L^2} = \int _t g(t)\overline{h(t)}\).

  2. 2.

    Note that the resulting visual representation is also known as spectrogram. However, for the reconstruction as discussed in the previous section, the phase factors of the coefficients are crucial and cannot be omitted.

  3. 3.

    We define the signal to noise ratio (SNR) by \(SNR_{dB} = 10\log _{10} (\Vert s\Vert _2^2 /\Vert f\Vert ^2_2)\), given in dB, by where \(f\) is the background signal, which can be seen as “noise” in which \(s\), the sound object is to be traced.

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Acknowledgments

We would like to thank Anaïk Olivero for sharing code for computing Gabor masks and Richard Kronland-Martinet and his team in LMA, CNRS Marseille, for giving us permission to use their software SPAD.

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Authors and Affiliations

  1. NuHAG, Faculty of Mathematics, University of Vienna, Vienna, Austria

    Monika Dörfler & Ewa Matusiak

Authors
  1. Monika Dörfler
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  2. Ewa Matusiak
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Corresponding author

Correspondence to Monika Dörfler .

Editor information

Editors and Affiliations

  1. CNRS - LMA, Marseille, France

    Mitsuko Aramaki

  2. Toulon-Var University and CNRS - LMA, Marseille, France

    Olivier Derrien

  3. CNRS - LMA, Marseille, France

    Richard Kronland-Martinet

  4. CNRS - LMA, Marseille, France

    Sølvi Ystad

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Dörfler, M., Matusiak, E. (2014). Sparse Gabor Multiplier Estimation for Identification of Sound Objects in Texture Sound. In: Aramaki, M., Derrien, O., Kronland-Martinet, R., Ystad, S. (eds) Sound, Music, and Motion. CMMR 2013. Lecture Notes in Computer Science(), vol 8905. Springer, Cham. https://doi.org/10.1007/978-3-319-12976-1_26

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  • DOI: https://doi.org/10.1007/978-3-319-12976-1_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12975-4

  • Online ISBN: 978-3-319-12976-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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