Download Simulation-Based Plate-Reverb Parameter Estimation from a Single Impulse Response ★ 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.
Download Sound Matching with a Differentiable Karplus-Strong Algorithm We present a self-supervised, event-based sound matching model using a differentiable extended Karplus-Strong algorithm. To avoid relying on external onset and fundamental frequency detectors, we explore training methodologies combining parameter losses on synthetic data with audio losses. We demonstrate that time-domain fractional delay interpolation provides gradient accuracy comparable to frequency-sampling while avoiding time-aliasing in highly resonant time-varying scenarios. Through systematic gradient analysis, we reveal that standard spectral losses provide no meaningful directional gradients for onset times, heavily degrading joint training. Training exclusively with parameter losses on synthetic data effectively learns fundamental frequency, timbral parameters, and onset times, but struggles to generalise to monophonic studio recordings of plucked guitar. External detectors combined with audio losses generalise best, isolating the model to timbre optimisation. While our Karplus-Strong decoder recovers interpretable parameters and naturally captures the transient characteristics of plucked guitar, Harmonics plus Noise baselines yield higher reconstruction fidelity by most metrics.
Download Quality Audio Prototyping: A Prototype System for Unified Sound Retrieval and Procedural Generation This paper presents Quality Audio Prototyping (QAP), a unified prototype system for sound retrieval and procedural generation. The system is designed to support rapid exploration of sound effects through a common interface that combines retrieval from existing audio collections with controllable procedural synthesis. By bringing these two paradigms together, QAP allows users to search for recorded sounds, generate new material, and iteratively refine results within a single workflow. The prototype emphasizes usability, extensibility, and practical sound-design applications, providing a foundation for future work on integrated retrieval and generation systems.
Download Band-Count Dense Modal Estimation with Fixed-Frequency Differentiable Resonator Refinement ★ Task B of the 1st DAFx Parameter Estimation Challenge requires estimating the frequencies, decay rates, gains, and number of modes in a dense plate-reverb impulse response. Weak and overlapping modes make sparse peak detection prone to severe undercounting. We train an ExtraTrees regressor on simulator-generated data to predict mode counts in four frequency bands. These counts define dense frequency grids, after which a differentiable all-pole resonator model refines decay and gain while keeping frequency fixed. On two separate synthetic validation sets, the system reduces a local challenge-style error by about 66% relative to the official default peak-picking baseline. The improvement is mainly associated with lower mode-count mismatch, while decay and gain remain the largest error sources. These findings support separating modal-density estimation from continuous parameter fitting.
Download Simulating Microphone Bleed and Tom-tom Resonance in Multisampled Drum Workstations In recent years multisampled drum workstations have become increasingly popular. They offer an alternative to recording a full drum kit if a producer, engineer or amateur lacks the equipment, money, space or knowledge to produce a quality recording. These drum workstations strive for realism, often recording up to a hundred different velocity hits of the same drum, including recordings from all microphones for each drum hit and including bleed between these microphones. This paper describes research undertaken to investigate if it is possible to simulate the snare and kick drum bleed into the tom-tom microphones and the subsequent resonance of the tom-tom that is caused, with the aim of reducing the amount of audio data that needs to be stored. A listening test was performed asking participants to identify the real recording from a simulation. The results were not statistically significant to reject the hypothesis that subjects were unable to distinguish the difference between the real and simulated recordings. This suggests listeners were unable to identify the real recording in the majority of cases.
Download Differentiable All-Pole Filters for Time-Varying Audio Systems Infinite impulse response filters are an essential building block of many time-varying audio systems, such as audio effects and synthesisers. However, their recursive structure impedes end-toend training of these systems using automatic differentiation. Although non-recursive filter approximations like frequency sampling and frame-based processing have been proposed and widely used in previous works, they cannot accurately reflect the gradient of the original system. We alleviate this difficulty by reexpressing a time-varying all-pole filter to backpropagate the gradients through itself, so the filter implementation is not bound to the technical limitations of automatic differentiation frameworks. This implementation can be employed within audio systems containing filters with poles for efficient gradient evaluation. We demonstrate its training efficiency and expressive capabilities for modelling real-world dynamic audio systems on a phaser, time-varying subtractive synthesiser, and feed-forward compressor. We make our code and audio samples available and provide the trained audio effect and synth models in a VST plugin1 .
Download Gradient Descent Optimization of Room Impulse Responses with Parameter-Efficient Differentiable Feedback Delay Networks Artificial reverberation can be produced either by convolving a signal with a measured room impulse response (RIR) or by synthesizing it with a parametric algorithm such as a Feedback Delay Network (FDN). The former reproduces a captured space faithfully but is costly to run and offers no control over its acoustic properties, while the latter is efficient and editable but hard to match to a specific room. In this paper we bridge the two by fitting a fully differentiable FDN to a measured RIR through gradient descent. The proposed network uses sixteen delay lines at a sampling rate of 48 kHz and trains all of its components jointly, including the delay lengths, the feedback matrix, the early-reflection taps, and a set of attenuation filters that control the frequency-dependent decay.