Using Tensor Factorisation Models to Separate Drums from Polyphonic Music

Derry Fitzgerald, Dublin Institute of Technology
Matt Cranitch, Cork Institute of Technology
Eugene Coyle, Dublin Institute of Technology

Document Type Conference Paper

Proceedings of the International Conference on Digital Audio Effects (DAFX09), Como, Italy, 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.