Clean2FX: Label-conditioned modeling for clean-to-effect guitar audio transformations
We present Clean2FX, a study and demo of label-conditioned clean-to-effect transformation for electric guitar audio. Given a clean guitar input and a target effect label, the task is to synthesize the corresponding effected signal while preserving the musical content. Training and evaluation pairs are constructed from EGFxSet real, single tone recordings by assembling matched clean/effected chords, melodies, and mixed timelines. This allows for controlled comparison across effects. We evaluate four neural approaches under a common spectrogram-based transformation setting: two variational autoencoders and two U-Net models that differ in whether they operate on linear or log-magnitude repre...
| Authors | Oliverio Bombicci Pontelli, Iran R. Roman |
|---|---|
| Primary category | cs.SD |
| Published | 9 July 2026 |
| Last updated at source | 9 July 2026 |
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