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International Symposium on I ndependent Component Analysis and Blind Source Separation, ICA 2004

Non-negative Matrix Factor Deconvolution ; Extracation of Multiple Sound Sources from Monophonic Inputs. International Symposium on I ndependent Component Analysis and Blind Source Separation, ICA 2004. Paris Smaragdis / Mitsubishi Electric Research Laboratories.

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International Symposium on I ndependent Component Analysis and Blind Source Separation, ICA 2004

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  1. Non-negative Matrix Factor Deconvolution;Extracationof Multiple Sound Sources from Monophonic Inputs International Symposium on Independent Component Analysis and Blind Source Separation, ICA 2004 Paris Smaragdis / Mitsubishi Electric Research Laboratories Presenter: Jain_De ,Lee

  2. Outline • Introduction • Non-negative Matrix Factorization • Non-negative Matrix Factor Deconvolution • Conclusions

  3. Introduction • Theory of TheOrigin • An extension to the Non-Negative Matrix Factorization algorithm • Identifying components with temporal structure Paatero (1997) Lee &Seung(1999)

  4. Non-negative Matrix Factorization • The Original Formulation of NMF [W] :Basis Functions Matrix [H] :Time Weights Matrix

  5. Non-negative Matrix Factorization • The Cost Function • Multiplicative Update Algorithm

  6. Non-negative Matrix Factorization • NMF for Sound Object Extraction STFT

  7. Non-negative Matrix Factorization

  8. Non-negative Matrix Factor Deconvolution • The Formulation of NMFD • The Operator Shifts The Columns ….

  9. Non-negative Matrix Factor Deconvolution • The Cost Function • The Update Rules ，where ，

  10. Non-negative Matrix Factor Deconvolution

  11. Non-negative Matrix Factor Deconvolution • In this example the drum sounds exhibit some overlap • at both time and frequency • Three types of drum sounds present into the scece • Sampled at 11.025 kHz • 256-point DFTs which were overlapping by 128-points • Performed for 3 basis functions

  12. Non-negative Matrix Factor Deconvolution • Reconstruction

  13. Conclusions • Pinpointed some of the shortcomings of conventional NMF when analyzing temporal patterns and presented an extension • Spectral bases have been used on spectrograms to extract sound objects from single channel sound scenes

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