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 ...
signal – source separation – audio – residual – monaural – music information retrieval – spectral filtering – semi-blind – underdetermined – multipitch estimation – note onset detection
Information
- Author
- Siamantas, Georgios
- Institution
- University of York
- Supervisor
- Publication Year
- 2009
- Upload Date
- Sept. 28, 2012
The current layout is optimized for mobile phones. Page previews, thumbnails, and full abstracts will remain hidden until the browser window grows in width.
The current layout is optimized for tablet devices. Page previews and some thumbnails will remain hidden until the browser window grows in width.