Download Nonlinear Strings based on Masses and Springs Due to advances in computational power, physical modelling for sound synthesis has gained an increased popularity over the past decades. Although much work has been done to accurately simulate existing physical systems, much less work exists on the use of physical modelling simply for the sake of creating sonically interesting sounds. This work presents a mass-spring network, inspired by existing models of the physical string. Masses have 2 translational degrees of freedom (DoF), and the springs have an additional equilibrium separation term, which together result in highly nonlinear effects. The main aim of this work is to create sonically interesting sounds while retaining some of the natural qualities of the physical string, as opposed to accurately simulating it. Although the implementation exhibits chaotic behaviour for certain choices of parameters, the presented system can create sonically interesting timbres, including nonlinear pitch glides and ‘wobbles’.
Download Differentiable All-Pass Filters for Phase Response Estimation and Automatic Signal Alignment Virtual analog (VA) audio effects are increasingly based on neural networks and deep learning frameworks. Due to the underlying black-box methodology, a successful model will learn to approximate the data it is presented, including potential errors such as latency and audio dropouts as well as non-linear characteristics and frequency-dependent phase shifts produced by the hardware. The latter is of particular interest as the learned phase-response might cause unwanted audible artifacts when the effect is used for creative processing techniques such as dry-wet mixing or parallel compression. To overcome these artifacts we propose differentiable signal processing tools and deep optimization structures for automatically tuning all-pass filters to predict the phase response of different VA simulations, and align processed signals that are out of phase. The approaches are assessed using objective metrics while listening tests evaluate their ability to enhance the quality of parallel path processing techniques. Ultimately, an overparameterized, BiasNet-based, all-pass model is proposed for the optimization problem under consideration, resulting in models that can estimate all-pass filter coefficients to align a dry signal with its affected, wet, equivalent.
Download Power-Balanced Dynamic Modeling of Vactrols: Application to a VTL5C3/2 Vactrols, which consist of a photoresistor and a light-emitting element that are optically coupled, are key components in optical dynamic compressors. Indeed, the photoresistor’s program-dependent dynamic characteristics make it advantageous for automatic gain control in audio applications. Vactrols are becoming more and more difficult to find, while the interest for optical compression in the audio community does not diminish. They are thus good candidates for virtual analog modeling. In this paper, a model of vactrols that is entirely physical, passive, with a program-dependent dynamic behavior, is proposed. The model is based on first principles that govern semi-conductors, as well as the port-Hamiltonian systems formalism, which allows the modeling of nonlinear, multiphysical behaviors. The proposed model is identified with a real vactrol, then connected to other components in order to simulate a simple optical compressor.
Download Antialiased State Trajectory Neural Networks for Virtual Analog Modeling In recent years, virtual analog modeling with neural networks experienced an increase in interest and popularity. Many different modeling approaches have been developed and successfully applied. In this paper we do not propose a novel model architecture, but rather address the problem of aliasing distortion introduced from nonlinearities of the modeled analog circuit. In particular, we propose to apply the general idea of antiderivative antialiasing to a state-trajectory network (STN). Applying antiderivative antialiasing to a stateful system in general leads to an integral of a multivariate function that can only be solved numerically, which is too costly for real-time application. However, an adapted STN can be trained to approximate the solution while being computationally efficient. It is shown that this approach can decrease aliasing distortion in the audioband significantly while only moderately oversampling the network in training and inference.
Download QUBX: Rust Library for Queue-Based Multithreaded Real-Time Parallel Audio Streams Processing and Management The concurrent management of real-time audio streams pose an increasingly complex technical challenge within the realm of the digital audio signals processing, necessitating efficient and intuitive solutions. Qubx endeavors to lead in tackling this obstacle with an architecture grounded in dynamic circular queues, tailored to optimize and synchronize the processing of parallel audio streams. It is a library written in Rust, a modern and powerful ecosystem with a still limited range of tools for digital signal processing and management. Additionally, Rust’s inherent security features and expressive type system bolster the resilience and stability of the proposed tool.
Download Auditory Discrimination of Early Reflections in Virtual Rooms This study investigates the perceptual sensitivity to early reflection changes across different spatial directions in a virtual
reality (VR) environment. Using an ABX discrimination paradigm, participants evaluated speech stimuli convolved with thirdorder Ambisonic room impulse responses under three position
reversal (Left–Right, Front–Back, and Floor–Ceiling) and three
reverberation conditions (RT60 = 1.0 s, 0.6 s, and 0.2 s). Binomial tests revealed that participants consistently detected early reflection differences in the Left–Right reversal, while discrimination performance in the other two directions remained at or near
chance. This result can be explained by the higher acuity and
lower localisation blur found for the human auditory system. A
two-way ANOVA confirmed a significant main effect of spatial
position (p = 0.00685, η² = 0.1605), with no significant effect of
reverberation or interaction. The analysis of the binaural room
impulse responses showed wave forms and Direct-ReverberantRatio differences in the Left–Right reversal position, aligning
with perceptual results. However, no definitive causal link between DRR variations and perceptual outcomes can yet be established.
Download Hyperbolic Embeddings for Order-Aware Classification of Audio Effect Chains Audio effects (AFXs) are essential tools in music production, frequently applied in chains to shape timbre and dynamics. The order of AFXs in a chain plays a crucial role in determining the final sound, particularly when non-linear (e.g., distortion) or timevariant (e.g., chorus) processors are involved. Despite its importance, most AFX-related studies have primarily focused on estimating effect types and their parameters from a wet signal. To
address this gap, we formulate AFX chain recognition as the task
of jointly estimating AFX types and their order from a wet signal.
We propose a neural-network-based method that embeds wet signals into a hyperbolic space and classifies their AFX chains. Hyperbolic space can represent tree-structured data more efficiently
than Euclidean space due to its exponential expansion property.
Since AFX chains can be represented as trees, with AFXs as nodes
and edges encoding effect order, hyperbolic space is well-suited
for modeling the exponentially growing and non-commutative nature of ordered AFX combinations, where changes in effect order can result in different final sounds. Experiments using guitar
sounds demonstrate that, with an appropriate curvature, the proposed method outperforms its Euclidean counterpart. Further analysis based on AFX type and chain length highlights the effectiveness of the proposed method in capturing AFX order.
Download A Virtual Analog Model of the Edp Wasp VCF In this paper we present a virtual analog model of the voltagecontrolled filter used in the EDP Wasp synthesizer. This circuit is an interesting case study for virtual analog modeling due to its characteristic nonlinear and highly dynamic behavior which can be attributed to its unusual design. The Wasp filter consists of a state variable filter topology implemented using operational transconductance amplifiers (OTAs) as the cutoff-control elements and CMOS inverters in lieu of operational amplifiers, all powered by a unipolar power supply. In order to accurately model the behavior of the circuit we propose extended models for its nonlinear components, focusing particularly on the OTAs. The proposed component models are used inside a white-box circuit modeling framework to create a digital simulation of the filter which retains the interesting characteristics of the original device.
Download A Virtual Instrument for Ifft-Based Additive Synthesis in the Ambisonics Domain Spatial additive synthesis can be efficiently implemented by applying the inverse Fourier transform to create the individual channels of Ambisonics signals. In the presented work, this approach has been implemented as an audio plugin, allowing the generation and control of basic waveforms and their spatial attributes in a typical DAW-based music production context. Triggered envelopes and low frequency oscillators can be mapped to the spectral shape, source position and source width of the resulting sounds. A technical evaluation shows the computational advantages of the proposed method for additive sounds with high numbers of partials and different Ambisonics orders. The results of a user study indicate the potential of the developed plugin for manipulating the perceived position, source width and timbre coloration.
Download A Coupled Resonant Filter Bank for the Sound Synthesis of Nonlinear Sources This paper is concerned with the design of efficient and controllable filters for sound synthesis purposes, in the context of the generation of sounds radiated by nonlinear sources. These filters are coupled and generate tonal components in an interdependent way, and are intended to emulate realistic perceptually salient effects in musical instruments in an efficient manner. Control of energy transfer between the filters is realized by defining a matrix containing the coupling terms. The generation of prototypical sounds corresponding to nonlinear sources with the filter bank is presented. In particular, examples are proposed to generate sounds corresponding to impacts on thin structures and to the perturbation of the vibration of objects when it collides with an other object. The different sound examples presented in the paper and available for listening on the accompanying site tend to show that a simple control of the input parameters allows to generate sounds whose evocation is coherent, and that the addition of random processes allows to significantly improve the realism of the generated sounds.