Authors: Felix Weninger, Alexander Lehmann, Björn Schuller
openBliSSART is a C++ framework and toolbox that provides “Blind Source Separation for Audio Recognition Tasks”. Its areas of application include, but are not limited to, 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 blind (unsupervised) source separation, it provides support for component classification by Support Vector Machines (SVM) using common acoustic features from speech and music processing. For component playback and data set creation, a Qt-based GUI is available. Furthermore, supervised NMF can be performed for source separation as well as 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. It is written in C++, enforcing strict coding standards, and adhering to modular design principles for seamless integration into multimedia applications.
Interfaces are provided to Weka and HTK (Hidden Markov Model Toolkit).
openBliSSART is free software and licensed under the GNU General Public License.
We provide a demonstrator that uses various features of openBliSSART to separate drum tracks from popular music. This demonstrator, along with extensive documentation, including a tutorial, reference manual, and description of the framework API, can be found in the openBliSSART source distribution.
If you want to use openBliSSART for your research, please cite the following paper: