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2011
IEEE

OpenBliSSART: Design and evaluation of a research toolkit for Blind Source Separation in Audio Recognition Tasks

8 years 11 months ago
OpenBliSSART: Design and evaluation of a research toolkit for Blind Source Separation in Audio Recognition Tasks
We describe and evaluate our toolkit openBliSSART (open-source Blind Source Separation for Audio Recognition Tasks), which is the C++ framework and toolbox that we have successfully used in a multiplicity of research on blind audio source separation and feature extraction. To our knowledge, it provides the first open-source implementation of a widely applicable algorithmic framework based on non-negative matrix factorization (NMF), including several preprocessing, factorization, and signal reconstruction algorithms for monaural signals. Apart from blind source separation using supervised and unsupervised NMF, we show how the framework is useful for the increasingly popular audio feature extraction methods by NMF. Furthermore, we point out a numerical optimization for NMF, and show that NMF source separation in real-time on a desktop PC is feasible with our implementation. We conclude with an evaluation of our toolkit on supervised speaker separation, demonstrating how our algorithmic...
Felix Weninger, Alexander Lehmann, Björn Schu
Added 20 Aug 2011
Updated 20 Aug 2011
Type Journal
Year 2011
Where ICASSP
Authors Felix Weninger, Alexander Lehmann, Björn Schuller
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