Bayesian group sparse learning for music source separation

  title={Bayesian group sparse learning for music source separation},
  author={Jen-Tzung Chien and Hsin-Lung Hsieh},
  journal={EURASIP J. Audio, Speech and Music Processing},
Nonnegative matrix factorization (NMF) is developed for parts-based representation of nonnegative signals with the sparseness constraint. The signals are adequately represented by a set of basis vectors and the corresponding weight parameters. NMF has been successfully applied for blind source separation and many other signal processing systems. Typically, controlling the degree of sparseness and characterizing the uncertainty of model parameters are two critical issues for model regularization… CONTINUE READING
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