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Musical Sound Source Separation Using Extended Tensor Decompositions, Derry Fitzgerald
Musical Sound Source Separation Using Extended Tensor Decompositions, Derry Fitzgerald
Conference papers
Recently, tensor decompositions have found use in sound source separation. In particular, non-negative tensor decompositions have received a lot of attention due to their ability to decompose audio spectrograms into meaningful ”parts” such as individual notes. Extensions to the basic non-negative tensor factorisation framework allow the incorporation of additional constraints, such as shift-invariance in both frequency and time. This enables the factorisations to capture more complex structures than individual notes, such as individual sources playing different pitches and time-evolving instrument timbres. Further music specific constraints such as harmonicity and source-filter modeling have been shown to improve separation performance for musical …
On The Use Of The Beta Divergence For Musical Source Separation, Derry Fitzgerald, Matt Cranitch, Eugene Coyle
On The Use Of The Beta Divergence For Musical Source Separation, Derry Fitzgerald, Matt Cranitch, Eugene Coyle
Conference papers
Non-negative Tensor Factorisation based methods have found use in the context of musical sound source separation. These techniques require the use of a suitable cost function to determine the optimal factorisation, and most work has focused on the use of the generalised Kullback-Liebler divergence, and more recently the Itakura-Saito divergence. These divergences can be regarded as limiting cases of the parameterised Beta divergence. This paper looks at the use of the Beta Divergence in the context of musical source separation with a view to determining an optimal value of Beta for this problem. This is considered for both magnitude and …