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Blind Source Separation for Audio Recognition Tasks
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openBliSSART is a C++ framework and toolbox that provides "Blind Source Separation for Audio Recognition Tasks". Its areas of application include instrument separation (e.g. extraction of drum tracks from popular music), speech enhancement, and feature extraction. It features various source separation algorithms, with a strong focus on variants of Non-Negative Matrix Factorization (NMF). Besides basic unsupervised source separation, it provides support for component classification by Support Vector Machines (SVM) using common acoustic features from speech and music processing. For data set creation a Qt-based GUI is available. Furthermore, supervised NMF can be performed and used for audio feature extraction. openBliSSART is fast: typical real-time factors are in the order of 0.1 (Euclidean NMF) on a state-of-the-art desktop PC. openBliSSART is free software and licensed under the GNU General Public License (see the COPYING file). Detailed installation instructions can be found in the INSTALL file. Make sure to read it first, as it contains valuable hints for easy installation on many system configurations. For a first impression of openBliSSART, you may want to try the drum beat separation demonstrator which is included in the "demo" directory, along with installation and usage information. There is a variety of documentation available in the "doc" directory, including a tutorial, reference manual, and API documentation. Please consult the file "doc/README" for details. If you want to use openBliSSART for your research, please cite the following paper: Felix Weninger, Alexander Lehmann, Bjoern Schuller: "openBliSSART: Design and Evaluation of a Research Toolkit for Blind Source Separation in Audio Recognition Tasks", to appear in Proc. International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2011, IEEE, Prague, Czech Republic, 22.-27.05.2011.