Memo 📔: Getting started with JUCE and Running Some Experiments for Neural Audio Synthesis

Several tries using JUCE from the basic demo and some of the generative machine learning applied for VST.

1. Install JUCE
2. AI audio processing libarary

If you are not familiar with JUCE, please follow official tutorial at first

Getting started

This tutorial shows you how to install JUCE and how to create a new cross-platform JUCE project using the Projucer. You also learn how to export the project to an IDE such as Xcode or Visual Studio to develop, run and debug your JUCE application. Beginner Windows, macOS, Linux, iOS, Android Download JUCE.

https://docs.juce.com/master/tutorial_new_projucer_project.html

You can download JUCE from here.

JUCE

Choose your download based on the platform you intend to start developing on.

https://juce.com/get-juce/download

Personally, I am using JUCE v7.0.4 atm.

Make sure your JUCE root directory and module directory from "Project>Global Paths"

Good explanation for CMake

CMake for JUCE Developers (#1): Why CMake?

Are you a JUCE developer making (or considering) the transition from the Projucer to CMake? In this new series, Ben Vining will walk through everything you need to know about CMake, from its use case to actually starting your first project.

https://youtu.be/FLP_AVbzueY

RAVE

GitHub - acids-ircam/rave_vst

Include RAVE models in your DAW for realtime deep learning based processing VST / AU / Standalone plugins available MacOS (M1 works, but you'll need to build yourself) & Unix (Windows build is still experimental at this point) Reconstruction & Prior modes available Click on the button with an arrow on the right to open / close the audio settings panel.

https://github.com/acids-ircam/rave_vst

DDSP VST

GitHub - magenta/ddsp-vst: Realtime DDSP Neural Synthesizer and Effect

VST3/AU plugins and desktop applications built using the JUCE framework and DDSP. Download the plugin binaries from here. Unzip and copy the two plugins (DDSP Effect and DDSP Synth) to their respective system folders: Audio Unit: /Library/Audio/Plug-Ins/Components VST3: /Library/Audio/Plug-Ins/VST3 Rescan for new plugins in your respective DAW (verified on Ableton/Logic Pro/FL Studio/Reaper).

https://github.com/magenta/ddsp-vst

DeepAFx-ST

GitHub - adobe-research/DeepAFx-ST: DeepAFx-ST - Style transfer of audio effects with differentiable signal processing. Please see https://csteinmetz1.github.io/DeepAFx-ST/

Style transfer of audio effects with differentiable signal processing 1 Centre for Digital Music, Queen Mary University of London 2 Adobe Research * Work performed in-part while an intern at Adobe Research. We present a framework that can impose the audio effects and production style from one recording to another by example with the goal of simplifying the audio production process.

https://github.com/adobe-research/DeepAFx-ST

GuitarML

GitHub - GuitarML/SmartGuitarAmp: Guitar plugin made with JUCE that uses neural networks to emulate a tube amplifier.

Guitar plugin made with JUCE that uses neural network models to emulate real world hardware. See video demo on YouTube This plugin uses a WaveNet model to recreate the sound of real world hardware. The current version models a small tube amp at clean and overdriven settings.

https://github.com/GuitarML/SmartGuitarAmp

Neural Amp Modeler Plug-in

GitHub - sdatkinson/NeuralAmpModelerPlugin: Plugin for Neural Amp Modeler

Plugin for Neural Amp Modeler. Contribute to sdatkinson/NeuralAmpModelerPlugin development by creating an account on GitHub.

https://github.com/sdatkinson/NeuralAmpModelerPlugin

GitHub - olilarkin/iPlug2OnnxRuntime: ML Audio plug-in example using iPlug2 & ONNX Runtime

ML Audio plug-in example using iPlug2 & ONNX Runtime - GitHub - olilarkin/iPlug2OnnxRuntime: ML Audio plug-in example using iPlug2 & ONNX Runtime

https://github.com/olilarkin/iPlug2OnnxRuntime

TCN sample code

Google Colaboratory

https://colab.research.google.com/drive/1gHZ-AEoYmfmWrjlKpKkK_SW1xzfxD24-?usp=sharing

A lightweight neural network inference engine written in C++

GitHub - jatinchowdhury18/RTNeural: Real-time neural network inferencing

Real-time neural network inferencing. Contribute to jatinchowdhury18/RTNeural development by creating an account on GitHub.

https://github.com/jatinchowdhury18/RTNeural

libtorch implementation example

GitHub - csteinmetz1/ronn: Randomized overdrive neural networks

Randomized overdrive neural networks. Contribute to csteinmetz1/ronn development by creating an account on GitHub.

https://github.com/csteinmetz1/ronn

Neutone SDK

GitHub - QosmoInc/neutone_sdk: Join the community on Discord for more discussions around Neutone! https://discord.gg/VHSMzb8Wqp

Join the community on Discord for more discussions around Neutone! https://discord.gg/VHSMzb8Wqp - GitHub - QosmoInc/neutone_sdk: Join the community on Discord for more discussions around Neutone! ...

https://github.com/QosmoInc/neutone_sdk