notebooks

Neural Audio Spring Reverb Notebooks

This directory contains the notebooks used for the preparatory work and to generate the plots and audio examples. If you want to re-run these notebooks you need to install some additional packages:

pip install essentia soundfile pyloudnorm

Table of Contents

3. Extract the audio features from the two dataset, save in multiple csv files available here.

• Visualize the extracted features on both datasets.

• Plot_Audio_Samples.ipynb A "service notebook" to plot the audio samples saved during training or evaluation runs and located in the audio directory.

Steerable discovery of neural audio effects

The preparatory work on the TCN model for this project is based on the paper Steerable discovery of neural audio effects by Christian J. Steinmetz and Joshua D. Reiss. My fork of the original repository contains the Jupyter notebooks related to the spring reverb: Steerable discovery of neural audio effects.