← 研踪 PaperTrailarXiv:2610.38740 · v1
Automated Parameter Sensitivity Ranking in Audio Synthesis
首次提交 2026-10-29 03:30
版本更新 2026-10-29 03:30
雷达观测 2026-10-30 10:22
摘要
Software synthesizers expose dozens of coupled controls, many of them redundant or perceptually inert at typical operating points. This paper presents a two-stage, measure-and-validate framework that ranks parameters by their influence on the audio output and then checks that ranking against an independent, variance-based experiment. Every rendered clip is normalized to -23 LUFS and described by five spectral fingerprints, so that gain shifts cannot masquerade as timbral change. The Sweep Test scores each parameter by spectral deviation over a 101-step sweep; the Sobol Test scores it by summed per-cell variance over a 128-point Sobol excitation. Across five architecturally distinct synthesizers (TorchSynth, Pyo, Pedalboard, Csound, and FluidSynth) spanning 48 to 76 parameters, the two tests agree at Spearman ρ= 0.82-0.96 (p-values \le 7.2 \times 10^{-15}) on the four engines that render deterministically, and at ρ= 0.32 on the one with process-level render noise--a diagnostic of that engine rather than of the method. The strong correlations survive reducing the Sobol budget from 128 to 32 points, and the complete analysis costs a one-time offline budget of about 66,000 renders.
作者备注：Submitted to the Journal of the Audio Engineering Society (JAES). 8 pages, 4 figures, 6 tables
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v1 · 2026-10-29 03:30 · 最新观测版本
Automated Parameter Sensitivity Ranking in Audio Synthesis
Software synthesizers expose dozens of coupled controls, many of them redundant or perceptually inert at typical operating points. This paper presents a two-stage, measure-and-validate framework that ranks parameters by their influence on the audio output and then checks that ranking against an independent, variance-based experiment. Every rendered clip is normalized to -23 LUFS and described by five spectral fingerprints, so that gain shifts cannot masquerade as timbral change. The Sweep Test scores each parameter by spectral deviation over a 101-step sweep; the Sobol Test scores it by summed per-cell variance over a 128-point Sobol excitation. Across five architecturally distinct synthesizers (TorchSynth, Pyo, Pedalboard, Csound, and FluidSynth) spanning 48 to 76 parameters, the two tests agree at Spearman ρ= 0.82-0.96 (p-values \le 7.2 \times 10^{-15}) on the four engines that render deterministically, and at ρ= 0.32 on the one with process-level render noise--a diagnostic of that engine rather than of the method. The strong correlations survive reducing the Sobol budget from 128 to 32 points, and the complete analysis costs a one-time offline budget of about 66,000 renders.
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