An experimental approach to generalized Wiener filtering in music source separation
This work addresses the extraction of high-quality component signals from drum solo recordings (breakbeats) for music production and remixing purposes. Specifically, we employ audio source separation techniques to recover sound events from the drum sound mixture corresponding to the individual drum strokes. Our separation approach is based on an informed variant of non-negative matrix factor deconvolution (NMFD) that has been proposed and applied to drum transcription and separation in earlier works. In this paper, we systematically study the suitability of NMFD and the impact of audio- and score-based side information in the context of drum separation. In the case of imperfect decompositions, we observe different cross-talk artifacts appearing during the attack and the decay segment of the extracted drum sounds. Based on these findings, we propose and evaluate two extensions to the core technique. The first extension is based on applying a cascaded NMFD decomposition while retaining selected side information. The second extension is a time--frequency selective restoration approach using a dictionary of single note drum sounds. For all our experiments, we use a publicly available data set consisting of multitrack drum recordings and corresponding annotations that allows us to evaluate the source separation quality. Using this test set, we show that our proposed methods improve the quality of the component signals.