Scyclone is an audio plugin that utilizes neural timbre transfer technology to offer a new approach to audio production. The plugin builds upon RAVE methodology, a realtime audio variational auto encoder, facilitating neural timbre transfer in both single and couple inference mode.
This enables a new artificial layering technique to be applied on the incoming signal in creating richer drum pallets, fuller atmospheres or simply transferring the timbre of the raw signal to another sound pallet. To further control the behaviour and production of the neural networks, we have internally equipped the plugin with signal processings modules allowing the user to shape, control and embellish the source and target timbres in a distinct manner.
Signal flow:
Scyclone offers an intuitive signal flow allowing for a seamless influence over inference and sound synthesis. The pre-processing modules are:
Additional in-built postprocessing modules permit for further manipulation and formation of the timbre transferred signal. The post-processing modules are:
Trained models:
We have provided two pre-trained models (presets) accessible under assets/models directory.
Detailed instructions can be found here:
Build with CMake
# clone the repository
git clone https://github.com/Torsion-Audio/Scyclone
cd Scyclone/
# initialize and set up submodules
git submodule update --init --recursive
# on macOS you might need to specify the processor type with -DCMAKE_HOST_SYSTEM_PROCESSOR=x86_64 or arm64
# on Windows currently only Release build works (add your own onnx static debug build in order to use debug)
cmake . -B cmake-build
cmake --build cmake-build --config Release
Notes:
Discover how to train your own RAVE-Models for Scyclone with our comprehensive step-by-step guide:
This project is subject to multiple licenses. The primary license for the entire project is the GNU General Public License version 3 (GPLv3), which is the most restrictive of all the licenses applied herein.
modules/RnboExport/
is licensed under the GPLv3assets/models/
are licensed under the Creative Commons Attribution-NonCommercial 4.0 International License