基于仿真的单脉冲响应板混响参数估计
Simulation-Based Plate-Reverb Parameter Estimation from a Single Impulse Response
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中文总结 AI 辅助
该研究针对第一届DAFx参数估计挑战赛Task A，提出仿真训练的非迭代集成树回归器估计板混响参数，其性能优于基线方法，推理成本更低。
中文摘要 AI 辅助
我们为第一届DAFx参数估计挑战赛的Task A提出了一种经仿真训练的非迭代估计器。每个未归一化的板混响脉冲响应由振幅、频谱和衰减描述符进行概括，集成树回归器一次性估计六个目标参数。在两个独立的合成验证集上，归一化模型的表现优于训练集均值及早期的原始回归基线。在共享集上，最终集成模型的表现还优于官方默认PSO的单次运行，且推理成本显著更低。由于官方标签隐藏，参数精度在模拟器匹配数据上进行测量，发布的响应仅支持音频侧一致性检查。该估计器返回无不确定性的点估计。
英文摘要
We present a simulation-trained, non-iterative estimator for Task A of the 1st DAFx Parameter Estimation Challenge. Each unnormalized plate-reverb impulse response is summarized by amplitude, spectral, and decay descriptors, and an ensemble of tree regressors estimates the six target parameters in one pass. Across two independent synthetic validation sets, the normalized models outperform the training-set mean and an earlier raw-regression baseline. On a shared set, the final ensemble also outperforms a single run of the official default PSO at substantially lower inference cost. Since the official labels are hidden, parameter accuracy is measured on simulator-matched data, and the released responses support only audio-side consistency checks. The estimator returns point estimates without uncertainty.
发表机构
- Queen Mary University of London（伦敦玛丽女王大学）
机构由 AI 辅助整理，请以论文原文为准。
