Research prototype

Record once.
Double it naturally.

Doubletracker is an experimental neural guitar doubler trained on real DI pairs. The goal is to generate a second performance of the same part, creating a stereo image that feels closer to real doubletracking than algorithmic doubling or widening.

The current model is still early, and reconstruction quality remains a work in progress.

01 / LISTEN

Current model examples

Compare the recorded references, the real doubletrack, and the model output. For the stereo mixes, use headphones or properly placed monitors.

Recorded GeneratedHeadphones recommended

Prototype note: All examples are currently limited to a 16 kHz sample rate. Recorded reference tracks pass through the same bandwidth-limited processing stage for a like-for-like comparison. Higher sample rates are planned as the model develops.

02 / CURRENT STATE

Still in development.

Doubletracker is currently a research prototype. The model already produces convincing doubletracking on some material, but quality and generalization are still being improved.

paired DI dataset
contributors
100 hdataset target

03 / CONTRIBUTE

Have double-tracked DI?

The most useful contribution is real, independently recorded doubletracks that you own—or have permission to provide for model training.