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Audio source separation with multiple microphones on time-frequency representations
2013
Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI
This paper presents various source separation methods that utilize multiple microphones. We classify them into two classes. Methods that fall into the first class apply independent component analysis (ICA) or Gaussian mixture model (GMM) to frequency bin-wise observations, and then solve the permutation problem to reconstruct separated signals. The second type of method extends non-negative matrix factorization (NMF) to a multimicrophone situation, in which NMF bases are clustered according to
doi:10.1117/12.2018632
fatcat:725lfo3lmrba7l6uca6gopfi3q