The code for multi-channel source separation and dereverberation such as FastMNMF1, FastMNMF2, and AR-FastMNMF2.
Tools for multi-channel sound source separation and dereverberation.
src
are listed belownumpy (1.19.2 was tested)
librosa
pysoundfile
tqdm
# optional packages
cupy # for GPU accelaration (9.4.0 was tested)
h5py # for saving the estimated parameters
torch # for using DNN source model in FastBSS2.py or FastMNMF2_DP.py
You can install all the packages above with pip install -r src/requirements.txt
src_torch
are listed belowtorch
torchaudio
tqdm
# optional packages
h5py # for saving the estimated parameters
You can install all the packages above with pip install -r src_torch/requirements.txt
python3 FastMNMF2.py [input_filename] --gpu [gpu_id]
If you use the code of FastMNMF1 or FastMNMF2 in your research project, please cite the following paper:
If you use the code of AR-FastMNMF2 in your research project, please cite the following paper: