Download Compiling Differentiable Audio Graphs to Real-Time DSP Differentiable audio processors are habitually designed and optimised in machine-learning frameworks, but deploying them as real-time audio effects still often requires non-automatic implementation in a dedicated digital signal processing language. The translation is error-prone, demands an onerous verification process, and detaches research prototypes from usable production tools. That being so, we present ADAC, a compiler that lowers a trained model to a framework-agnostic intermediate representation and emits efficient FAUST code whose impulse response matches the source model to within floating-point arithmetic noise, direct paths included. The optimisation loop is made audible by replacing the model in a running plugin after each gradient step. The exported processor carries a small set of macro-controls that leave its stability intact. A stability certificate computed from the shipped parameters is checked before the plugin is built. At the demonstration, a feedback delay network is trained and exported to a working plugin.
Download ALAMODE: Automated Learning of Acoustical Modal Parameters via Differential Evolution This paper is a technical report on the methodology submitted for Task A of the 1st DAFx Parameter Estimation Challenge. The goal of the challenge’s task is to invert the multi-dimensional physical and geometric parameters of a virtual plate reverberator given a target reference impulse response. To achieve this, we present a multi-stage gradient-free optimization framework. This three-stage optimization is computed using an efficient physics-based simulator, starting with an optimization of only mode frequency-determining physical parameters, followed by a 6-DoF parameter optimization with position-determining ones and a final phase for frequency- and position-independent mode amplitude estimation.
Download Multi-View Subband Autoregressive Pole Harvesting for Modal Plate Identification We describe a Task B submission for the 1st DAFx Parameter Estimation Challenge. A matching-pursuit anchor stage seeds a multi-view subband autoregressive (AR) pole harvester on the raw IR and its first two finite differences; since linear filtering preserves pole locations while changing residues, the three views expose complementary subsets of the same pole set. Bands in which the AR order saturates are recursively split, and any remaining under-resolved region is completed from an IR-derived saturation indicator. Gains are assigned by a global ridge least-squares (LS) fit in the damped-biquad atom convention. The pipeline uses only the unnormalized IR; so it does not use plate parameters, analytical modal-frequency or decay laws, .wav files, or Task A information.