Non negative sparse representation for Wiener based source separation with a single sensor


We propose a new method to perform the separation of two sound sources from a single sensor. This method generalizes the Wiener filtering with locally stationary, non gaussian, parametric source models. The method involves a learning phase for which we propose three different algorithm. In the separation phase, we use a sparse non negative decomposition algorithm of our own. The algorithms are evaluated on the separation of real audio data.

DOI: 10.1109/ICASSP.2003.1201756

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Extrapolation, interpolation and smoothing of stationary time series

  • N Wiener
  • 1949
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