Download Using tensor factorisation models to separate drums from polyphonic music 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.
Download An Efficient Phasiness Reduction Technique for Moderate Audio Time-Scale Modification Phase vocoder approaches to time-scale modification of audio introduce a reverberant/phasy artifact into the time-scaled output due to a loss in phase coherence between short-time Fourier transform (STFT) bins. Recent improvements to the phase vocoder have reduced the presence of this artifact, however, it remains a problem. A method of time-scaling is presented that results in a further reduction in phasiness, for moderate time-scale factors, by taking advantage of some flexibility that exists in the choice of phase required so as to maintain horizontal phase coherence between related STFT bins. Furthermore, the approach leads to a reduction in computational load within the range of time-scaling factors for which phasiness is reduced.