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Brand profile · USA, est. 2020

GuitarML

GuitarML is an open-source project developing neural network-based guitar amplifier and pedal emulations. The project uses machine learning models trained on recordings of real guitar hardware to produce remarkably accurate software emulations of specific amplifiers and effects pedals. GuitarML has built a community of contributors sharing neural network models for various guitar hardware, making accurate amp and pedal emulation available as a free open-source resource. The project sits at the exciting frontier of machine learning applied to guitar tone capture.

Neural network guitar amp emulationOpen-source machine learning-based pedal captureCommunity-contributed neural network model libraryFree guitar hardware emulation through deep learning
2020founded
USAcountry
2products in stock
Freewaresegment

All 2 GuitarML products

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GuitarML, honestly

What GuitarML does well
  • Remarkably accurate hardware emulation through machine learning
  • Completely free and open-source
  • Growing community library of hardware neural network models
  • Cutting-edge application of deep learning to guitar tone
  • Enables accurate capture of any guitar hardware
What to watch for
  • Requires technical understanding to use fully
  • UI design is minimal as an open-source project
  • Less polished than commercial amp sims from Neural DSP or IK Multimedia
  • Hardware capture quality varies by model contributor

Questions about GuitarML

Where is GuitarML based?

GuitarML is an open-source project primarily developed by Keith Bloemer in the USA, with contributions from the broader audio developer community.

Is GuitarML good for beginners?

The concept is approachable — loading existing models is easy — but creating new neural network captures requires technical knowledge.

What is GuitarML best known for?

GuitarML is best known for applying neural network machine learning to guitar amplifier and pedal emulation, providing free and open-source accurate hardware tone capture.

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