Doping audio signals for source separation

This work fits in the frames of sparse component analysis (SCA), informed source separation (ISS) and doping watermarking. The SCA relies on a strong hypothesis of sparsity of the sources. In a particular context where the original sources are available (ISS), we make the distributions of the time-f...

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Bibliographic Details
Main Authors: Mahe, G., Nadalin, E. Z., Romano, J. T.
Format: Conference Proceeding
Language:English
Subjects:
audio
Doping
doping watermarking
Estimation
Histograms
informed source separation (ISS)
Source separation
sparse component analysis (SCA)
Speech
Time frequency analysis
Watermarking
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Summary:This work fits in the frames of sparse component analysis (SCA), informed source separation (ISS) and doping watermarking. The SCA relies on a strong hypothesis of sparsity of the sources. In a particular context where the original sources are available (ISS), we make the distributions of the time-frequency coefficients of the sources more sparse, through a doping watermarking that imperceptibly transform the histogram of the coefficients. Using the "sparsified" sources instead of the original ones in a SCA leads to a better estimation of the number of sources and to a more accurate identification of the mixing system.
ISSN:2219-5491
2219-5491