Example:
Using the provided toydata:
$./mirapie.py toydata/ toydata/initL.csv -p 1 -m 1
Using a your multitrack dataset, e.g. in ../path/to/dataset and the interference matrix in ../path/to/matrix.csv.
$./mirapie.py ../path/to/dataset/ ../path/to/matrix.csv -p 1 -m 3
1 Setup the virtual enviroment, run it and install all the dependencies
$ virtualenv venv -p python3
$ source venv/bin/activate
$ pip install -r requirements
$ ./mirapie.py -h
MIRAPIE: Multitrack Interference RemovAl for full-lenght live recordings
usage:
mirapie.py path-to-wavs csv-matrix [-h] [-l MATRIX] [-p PRESET] [-m MODE]
Python implementation for MIRA
positional arguments:
path-to-wavs location of the multitrack recordings [.wav]
csv-matrix name of the initial interference matrix [.csv]
optional arguments:
-h, --help show this help message and exit
-l MATRIX, --matrix MATRIX
L matrix file (default: None)
-p PRESET, --preset PRESET
select one of the possible preset (default: 1)
-m MODE, --mode MODE select one of the possible mode (default: 0)
path-to-wavs : folder containing the audio recording in [.wav]
csv-matrix : file containing info about mic channels and instrumens organized in a table [.csv]
-p PRESET : present number in the user-editable yaml file preset.yml
-m MODE : mode of the algorithm, 1 one chunk, 2 one chunk with random projection, 3 full-length with random projection.
advance algorithm parameters in preset.yml file
Diego Di Carlo (Chutlhu)
- Works only with Python3
- Conference paper about mirapie can be downloaded here
- Special thanks to Antoine Liutkus and Thomas Praetzlich and Multispeech Team at INRIA GRAND EST.
- check the github repo mirapieDev
- please write to
[email protected]for any questions
GPL v3