Sound Signal Processing and BioSound.
The package has routines to perform signal analysis on time series and sond waveforms in particular. It includes: Spectrogram Modulation Power Spectrum Coherence Filtering Power spectrum Fundamental Estimation
The BioSound class is used to represent a biological sound (natural sound) with multiple feature spaces that include classical bioacoustical predefined acoustical features (pitch, formants, spectral mean and quartiles, rms, etc) as well as the full spectrogram and the modulation power spectrum.
The plotDiscriminate function in discriminate.py performs cross-validated supervised and regularized classification. It can be used in conjunction with BioSound features to describe differences across groups of sounds.
You can download from github or pip install: pip install soundsig Downloading the files will take seconds.
soundsig requires the python typical packages matplotlib, numpy, scikit-learn, h5py. All of these will be automatically installed during the pip install. The code was originally written for Python 2.7 but updated for Python 3.
Tutorials come in the form of 4 Jupyter Notebooks that can be found at theunissenlab/BioSoundTutorials