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Spectral similarity metrics for sound source formation based on the common variation cue

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Abstract

Scene analysis is a relevant way of gathering information about the structure of an audio stream. For content extraction purposes, it also provides prior knowledge that can be taken into account in order to provide more robust results for standard classification approaches. In order to perform such scene analysis, we believe that the notion of temporality is important. Consequently, we study in this paper a new way of modeling the evolution over time of the frequency and amplitude parameters of spectral components. We evaluate its benefits by considering its ability to automatically gather the components of the same sound source. The evaluation of the proposed metric shows that it achieves good performance and takes better account of micro-modulations.

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Acknowledgements

This work has been initiated when the authors were at the LaBRI (UMR-Cnrs 5800, University of Bordeaux 1) and has been partly funded by the OSEO project Quaero within the task 6.4: “Music Search by Similarity” and the French GIP ANR DESAM under contract ANR-06-JCJC-0027-01.

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Authors and Affiliations

  1. Telecom ParisTech, 46, rue Barrault, 75634, Paris Cedex 13, France

    Mathieu Lagrange

  2. Linköping University, Bredgatan 33, 60174, Norrköping, Sweden

    Martin Raspaud

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  1. Mathieu Lagrange
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  2. Martin Raspaud
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Correspondence to Mathieu Lagrange.

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Lagrange, M., Raspaud, M. Spectral similarity metrics for sound source formation based on the common variation cue. Multimed Tools Appl 48, 185–205 (2010). https://doi.org/10.1007/s11042-009-0382-9

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