Download DAFx Challenge Introduction & Results The 1st DAFx Parameter Estimation Challenge is an open initiative to advance the state of the art in parameter estimation for acoustic modeling. Stated as a system identification problem, this first edition focuses on plate reverberation—an archetypal dense, modal and weakly damped acoustic system. Participants tackled two tasks: (A) estimating the physical parameters of a vibrating plate from its impulse response, and (B) recovering the modal parameters of the same system. Both rest on a simulation framework based on the damped Kirchhoff–Love plate equation, and both are posed and scored entirely on synthetic data produced by that framework: no measurement of a real plate is involved. Two participants solved Task A down to machine precision by different strategies: one a neural network trained on a very large dataset, and one gradient-free optimization with many inexpensive evaluations. Task B proved considerably harder: the best submission attains a relative error of 0.33 on a [0, 2] scale, and every method recovers modal frequencies and decay rates far more accurately than modal gains. A complementary frequency-domain evaluation reorders the ranking and exposes a systematic gain bias to which the per-mode metric is blind.
Download Power-Balanced Drift Regulation for Scalar Auxiliary Variable Methods: Application to Real-Time Simulation of Nonlinear String Vibrations Efficient stable integration methods for nonlinear systems are
of great importance for physical modeling sound synthesis. Specifically, a number of musical systems of interest, including vibrating
strings, bars or plates may be written as port-Hamiltonian systems
with quadratic kinetic energy and non-quadratic potential energy.
Efficient schemes have been developed for such systems through
the introduction of a scalar auxiliary variable. As a result, the stable real-time simulations of nonlinear musical systems of up to a
few thousands of degrees of freedom is possible, even for nearly
lossless systems. However, convergence rates can be slow and
seem to be system-dependent. Specifically, at audio rates, they
may suffer from numerical drift of the auxiliary variable, resulting
in dramatic unwanted effects on audio output, such as pitch drifts
after several impacts on the same resonator.
In this paper, a novel method for mitigating this unwanted drift
while preserving power balance is presented, based on a control
approach. A set of modified equations is proposed to control the
drift artefact by rerouting energy through the scalar auxiliary variable and potential energy state. Numerical experiments are run
in order to check convergence on simulations in the case of a cubic nonlinear string. A real-time implementation is provided as
a Max/MSP external. 60-note polyphony is achieved on a laptop, and some simple high level control parameters are provided,
making the proposed implementation suitable for use in artistic
contexts. All code is available in a public repository, along with
compiled Max/MSP externals1.
Download A hybrid approach to timbral consistency in a virtual instrument The aim of this work is to make an instrument that is timbrally consistent over pitch and loudness. This particular work is not attempting to reproduce an existing instrument’s timbre, but to produce a timbrally dynamic virtual instrument that can be designed by the user. In this paper there is a brief introduction to timbre and synthesis methods, followed by a proposal on how to make timbrally consistent virtual instruments out of given timbres.
Download Gestural Auditory and Visual Interactive Platform This paper introduces GAVIP, an interactive and immersive platform allowing for audio-visual virtual objects to be controlled in real-time by physical gestures and with a high degree of intermodal coherency. The focus is particularly put on two scenarios exploring the interaction between a user and the audio, visual, and spatial synthesis of a virtual world. This platform can be seen as an extended virtual musical instrument that allows an interaction with three modalities: the audio, visual and spatial modality. Intermodal coherency is thus of particular importance in this context. Possibilities and limitations offered by the two developed scenarios are discussed and future work presented.
Download Neural Networks for Physical Parameter Estimation of Plate Reverberation from Impulse Responses ★ This paper presents our Task A submission to the 1st DAFx Parameter Estimation Challenge. We use the official ModalPlate dataset generator to synthesize 1000 one-second plate impulse responses with randomly sampled parameters inside the public ranges. A time-domain CNN-GRU regressor then estimates the six official Task A parameters from each unnormalised waveform. The model combines three one-dimensional convolutional blocks with a bidirectional gated recurrent unit and is trained with mean squared error on min-max normalised targets. The generated data are split into 700/150/150 train/validation/test examples, and the test split is never used during training or model selection. The implementation follows the official Task A format and exports evaluation-compatible prediction files for both development evaluation and blind-set submission.
Download Toward the Perfect Audio Morph? Singing Voice Synthesis and Processing This paper reviews the popular methods and models used for the synthesis of the singing voice, discussing strengths and weaknesses of each technique. Then a brief review is given of research on cross-modal visual/auditory perception of the human voice. The paper concludes with comments related to the singing synthesis systems discussed, addressing multi-modal perception, audio morphing, and the categorical perception of sound.
Download Multi-Source Extension and Hyperparameter Optimization of the DiffRIR Framework for Room Impulse Response Synthesis Efficient prediction of Room Impulse Responses (RIRs) is a cornerstone for immersive virtual acoustics and scalable room acoustic modeling. This study extends the DiffRIR framework – proposed by Wang et al. in Hearing Anything Anywhere – by introducing a multi-source training logic and systematically optimizing its convergence behavior to overcome the inherent limitations of the original framework. Our results reveal that multi-source training acts as implicit data augmentation, where the resulting increase in spatial entropy enhances the model's spectral accuracy. Furthermore, we demonstrate that the model exhibits remarkable robustness against geometric inaccuracies, maintaining numerical stability even with source positional offsets of up to 4 m in single-source baseline evaluations. By identifying a learning rate of 3×10⁻², we were able to reduce the training duration to 23% of the original baseline without compromising prediction accuracy. While the increased complexity of multi-source fields necessitates a trade-off in temporal precision – quantified via our newly integrated Energy Decay Convergence (EDC) metric – this research provides an efficient and resilient solution for acoustic simulations in complex environments.
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 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 Identification and Modeling of a Flute Source Signal This paper addresses the modeling of the source signal of a flute sound obtained by «removing» the contribution of the resonator. The resulting sound has then a more regular spectral behavior and can be modeled using signal models. The decomposition of the source signal into a deterministic and a stochastic part has been made using adaptive filtering. The deterministic part can then be modeled by non-linear synthesis models, the parameters of which are obtained using perceptive criteria. Linear filtering are used to model the stochastic part of the source signal.