Evaluating Loss Functions in Differentiable Out-of-Domain Sound-Matching with Partial Parameter Distance
In out-of-domain (OOD) sound-matching, a synthesizer is optimized to mimic a sound it did not generate. OOD evaluation of loss functions is underexplored in part because the standard "parameter loss" metric requires a shared parameter space between target and imitator, which OOD settings lack. We introduce Partial Parameter Distance (PPD), which applies parameter loss only to the critical parameters that mismatched synthesizers share (e.g., filter cutoffs), enabling automatically evaluated OOD experiments; we verify its results with blinded listening tests. Across seven scenarios involving band-pass filtering, amplitude modulation, and pitch-bending, we evaluate four differentiable loss f...
| Authors | Amir Salimi, Daniel Penner, Kalvin Eng et al. |
|---|---|
| Primary category | cs.SD |
| Published | 27 August 2026 |
| Last updated at source | 27 August 2026 |
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