An iterative, residual-based approach to unsupervised musical source separation in single-channel mixtures (2009)
Abstract / truncated to 115 words
This thesis concentrates on a major problem within audio signal processing, the separation of source signals from musical mixtures when only a single mixture channel is available. Source separation is the process by which signals that correspond to distinct sources are identified in a signal mixture and extracted from it. Producing multiple entities from a single one is an extremely underdetermined task, so additional prior information can assist in setting appropriate constraints on the solution set. The approach proposed uses prior information such that: (1) it can potentially be applied successfully to a large variety of musical mixtures, and (2) it requires minimal user intervention and no prior learning/training procedures (i.e., it is an unsupervised ... toggle 11 keywordssignal – source separation – audio – residual – monaural – music information retrieval – spectral filtering – semi-blind – underdetermined – multipitch estimation – note onset detection
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