Simulation-Based Inference for Plate Reverb System Identification
We address Task A of the 1st DAFx Parameter Estimation Challenge, which aims to retrieve the physical parameters of a plate model from an impulse response. To do so, we use the Simulation-Based Inference (SBI) framework, in which we train a neural network to estimate a density over plate parameters given an impulse response, using a dataset generated by the simulator. Inference for a new impulse response then requires only a forward pass through the network, without involving the simulator. For each test observation, we fine-tune a specific network: additional simulation rounds are performed by sampling parameters from the current estimated distribution, simulating the corresponding impul...
| Authors | Dylan Sechet, Marc Evrard, Matthieu Kowalski |
|---|---|
| Primary category | eess.AS |
| Published | 28 September 2026 |
| Last updated at source | 28 September 2026 |
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