This repository aims at feature extraction from WAV files.
The following features can be extracted:
- MFCCs
- Delta-MFCCs (1st and 2nd order)
Additionally, the following information is retrieved from the audio files:
- file name
- duration of the audio
- number of samples
- sampling rate
It is recommended that you use Python 3.8 to set up your virtualenv (see setup section).
The following dependencies will be installed:
- librosa (0.8.0)
For the setup of this repository simply type:
make
This will
- set up a virtual environment for this repository,
- install all necessary project dependencies.
If this does not work, make sure you have the package virtualenv
installed for your python interpreter (pip install virtualenv
).
To have features extracted from a series of WAV files, extract_mfcc.py
takes a list of file names as an argument.
For example:
python3 extract/extract_mfcc.py path/file1.wav path/file2.wav
For all files in a directory:
python3 extract/extract_mfcc.py path/*
To reset the repository to its inital state, type:
make dist-clean
This will remove the virtual environment and all its dependencies.
With the make
command you can re-install them.
To remove temporary files like .pyc or .pyo files, type:
make clean