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Merge pull request #12 from GuitarML/v1-5-updates
V1 5 updates
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Guitar plugin made with JUCE that uses neural network models to emulate real world hardware. | ||
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Checkout the tutorial on [YouTube](https://youtu.be/HrNf6DNRUdU) for creating your own models for the SmartPedal. | ||
- Checkout the tutorial on [YouTube](https://youtu.be/HrNf6DNRUdU) for creating your own models for the SmartPedal. | ||
- Visit the GuitarML [ToneLibrary Website](https://guitarml.com/tonelibrary/tonelib-sa.html) to download SmartPedal compatible models. | ||
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![app](https://github.com/GuitarML/SmartGuitarPedal/blob/master/resources/app_pic.png) | ||
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This plugin uses a WaveNet model to recreate the sound of real world hardware, such as | ||
a TS9 Tubescreamer or Blues Jr amp. Drive and Level are used for simple ways to | ||
control the sound. The WaveNet model is effective at emulating distortion style effects or tube amplifiers. | ||
a TS9 Tubescreamer or Blues Jr amp. Drive and Level adjust the signal gain before and after the | ||
WaveNet model processing. As of version 1.5, the SmartPedal can run models conditioned on a single parameter, | ||
such as a gain control. When conditioned models are loaded, the LED graphic will change colors | ||
from red to blue, and the Drive knob will control the conditioned parameter. | ||
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![app](https://github.com/keyth72/SmartGuitarPedal/blob/master/resources/app_pic.png) | ||
The WaveNet model is effective at emulating distortion style effects or tube amplifiers, but cannot capture | ||
time based effects such as reverb or delay. You can capture the sound of an amplifier either by recording with | ||
a microphone, or direct out from a load box. When running "Direct Out" models, you will need to use an | ||
Impulse Response plugin to accurately model the amp speaker/cabinet. | ||
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You can create your own models and load them in SmartGuitarPedal using the [PedalNetRT](https://github.com/GuitarML/PedalNetRT) repository. | ||
You can create your own models and load them in SmartGuitarPedal using the [PedalNetRT](https://github.com/GuitarML/PedalNetRT) repository directly, or | ||
by using the Capture Utility files (available for download at [GuitarML.com](https://guitarml.com/)) with Google Colab and following the [Video Tutorial](https://youtu.be/HrNf6DNRUdU). | ||
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Model training is done using PyTorch on pre recorded .wav samples. More info in the above repository. | ||
To share your best models, email the json files to [email protected] and they may be included | ||
in the latest release as a downloadable zip. | ||
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in the latest [ToneLibrary](https://guitarml.com/tonelibrary/tonelib-sa.html) release. | ||
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Also see companion plugin, the [SmartGuitarAmp](https://github.com/GuitarML/SmartGuitarAmp) | ||
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This project is licensed under the Apache License, Version 2.0 - see the [LICENSE](LICENSE) file for details. | ||
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This project builds off the work done in the [WaveNetVA](https://github.com/damskaggep/WaveNetVA) repository. | ||
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### Special Thanks | ||
Special thanks to Stefan Schmidt for the graphics in SmartPedal version 1.5. These were created from a Blender model and rendered using the Cycles render engine. |
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