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User Assisted Source Separation Using Non-Negative Matrix Factorisation, Derry Fitzgerald
User Assisted Source Separation Using Non-Negative Matrix Factorisation, Derry Fitzgerald
Conference papers
Much research has been carried out on the use of non-negative matrix factorisation for the purpose of musical sound source separation. However, a notable shortcoming of non-negative matrix factorisation is that the recovered basis functions have to be clustered to sound sources for separation to take place. This has proved to be a difficult problem to solve. As a means of overcoming this problem, we introduce an extension to non-negative matrix factorisation which allows a user to guide the sepa- ration by singing, or playing along with, the source they want to separate. This is done through the use of …
Shifted Nmf Using An Efficient Constant-Q Transform For Monaural Sound Source Separation, Rajesh Jaiswal, Derry Fitzgerald, Eugene Coyle, Scott Rickard
Shifted Nmf Using An Efficient Constant-Q Transform For Monaural Sound Source Separation, Rajesh Jaiswal, Derry Fitzgerald, Eugene Coyle, Scott Rickard
Conference papers
Non-negative Matrix Factorisation (NMF) based algorithms have found application in monaural audio source separation due to their ability to factorize audio spectrogram into additive part-based basis functions, which typically corresponds to individual notes or chords in music. These separated basis functions are usually greater in number than the active sources, hence clustering is needed for individual source signal synthesis. Although, many attempts have been made to improve the clustering of the basis functions to sources, much research is still required in this area. Recently, Shifted NMF based methods have been proposed as a means to avoid clustering these pitched basis …