Audio source separation with multiple microphones on time-frequency representations

Hiroshi Sawada

doi:10.1117/12.2018632

29 May 2013 Audio source separation with multiple microphones on time-frequency representations

Hiroshi Sawada

Proceedings Volume 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI; 875007 (2013) https://doi.org/10.1117/12.2018632
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

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 their spatial properties. We have a unified understanding that all methods analyze a time-frequency representation with an additional microphone axis.

Citation Download Citation

Hiroshi Sawada "Audio source separation with multiple microphones on time-frequency representations", Proc. SPIE 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI, 875007 (29 May 2013); https://doi.org/10.1117/12.2018632

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