Flexible Audio Source Separation Toolbox
Speed up the conception and automate the implementation of new model-based audio source separation algorithms.
- LGM, NMF, GMM, GSMM, HMM, HSMM (NMF is the only model available in the C++ version of the toolbox)
- Source-filter models
- Rank-1 and full-rank spatial models
- Any combination of the models above
- version 3.0.0 (Inria license - August 2019) with core in C++ and user scripts in Matlab and Python (by Y. Salaün, E. Vincent, E. Camberlein, R. Lebarbenchon, R. Gribonval and N. Bertin).
For academic research activities only, this Software is freely available under the terms of the following license agreement (download link). To obtain the Software source code, please fill in (items in blue boxes), sign and send two signed copies of this license agreement to:
- For all other uses, the software is available under an Inria commercial license. Please contact email@example.com
- version 2.2.2 (QPL license - May 2018) with core in C++ and user scripts in Matlab and Python (by Y. Salaün, E. Vincent, E. Camberlein, R. Lebarbenchon and N. Bertin)
- version 1 (GPL license) for Matlab (800 KB) and user guide (250 KB) (by A. Ozerov, E. Vincent and F. Bimbot)
- pyFASST for Python (by J.-L. Durrieu)
- Y. Salaün, E. Vincent, N. Bertin, N. Souviraà-Labastie, X. Jaureguiberry, D. T. Tran, and F. Bimbot, The Flexible Audio Source Separation Toolbox Version 2.0, in Show & Tell, IEEE International Conference on Acoustics, Speech and Signal Processing, 2014.
- A. Ozerov, E. Vincent, and F. Bimbot, A general flexible framework for the handling of
prior information in audio source separation, IEEE Transactions on Audio, Speech and Signal Processing 20(4), pp. 1118-1133 (2012).
Source separation examples