Using Tensor Factorisation Models to Separate Drums from Polyphonic Music
Derry Fitzgerald, Matt Cranitch, Eugene D. Coyle · Arrow@dit (Dublin Institute of Technology) · 2009
This paper describes the use of Non-negative Tensor Factorisation models for the separation of drums from polyphonic audio. Improved separation of the drums is achieved through the incorporation of Gamma Chain priors into the Non-negative Tensor Factorisation framework. In contrast to many previous approaches, the method used in this paper requires little or no pre-training or use of drum templates. The utility of the technique is shown on real-world audio examples.