Sound Source Separation Using Shifted Non-Negative Tensor Factorisation
Derry Fitzgerald, Matt Cranitch, Edward J. Coyle · 2006
Recently, shifted non-negative matrix factorisation was developed as a means of separating harmonic instruments from single channel mixtures. However, in many cases two or more channels are available, in which case it would be advantageous to have a multichannel version of the algorithm. To this end, a shifted non-negative tensor factorisation algorithm is derived, which extends shifted non-negative matrix factorisation to the multi-channel case. The use of this algorithm for multi-channel sound source separation of harmonic instruments is demonstrated. Further, it is shown that the algorithm can be used to perform non-negative tensor deconvolution, a multi-channel version of non-negative matrix deconvolution, to separate sound sources which have time evolving spectra from multi-channel signals