Paper Archive

In this paper, a complete simulation of a trombone using finitedifference time-domain (FDTD) methods is proposed. In particular, we propose the use of a novel method to dynamically vary the number of grid points associated to the FDTD method, to simulate the fact that the physical dimension of the trombone’s resonator dynamically varies over time. We describe the different elements of the model and present the results of a real-time simulation.

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For physical modelling sound synthesis, many techniques are available; time-stepping methods (e.g., finite-difference time-domain (FDTD) methods) have an advantage of flexibility and generality in terms of the type of systems they can model. These methods do, however, lack the capability of easily handling smooth parameter changes while retaining optimal simulation quality and stability, something other techniques are better suited for. In this paper, we propose an efficient method to smoothly add and remove grid points from a FDTD simulation under sub-audio rate parameter variations. This allows for dynamic parameter changes in physical models of musical instruments. An instrument such as the trombone can now be modelled using FDTD methods, as well as physically impossible instruments where parameters such as e.g. material density or its geometry can be made time-varying. Results show that the method does not produce (visible) artifacts and stability analysis is ongoing.

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Sustained contact interactions like scraping and rolling produce a wide variety of sounds. Previous studies have explored ways to synthesize these sounds efficiently and intuitively but could not fully mimic the rich structure of real instances of these sounds. We present a novel source-filter model for realistic synthesis of scraping and rolling sounds with physically and perceptually relevant controllable parameters constrained by principles of mechanics. Key features of our model include non-linearities to constrain the contact force, naturalistic normal force variation for different motions, and a method for morphing impulse responses within a material to achieve location-dependence. Perceptual experiments show that the presented model is able to synthesize realistic scraping and rolling sounds while conveying physical information similar to that in recorded sounds.

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This paper addresses identification of nonlinear circuits for power-balanced virtual analog modeling and simulation. The proposed method combines a port-Hamiltonian system formulation with kernel-based methods to retrieve model laws from measurements. This combination allows for the estimated model to retain physical properties that are crucial for the accuracy of simulations, while representing a variety of nonlinear behaviors. As an illustration, the method is used to identify a nonlinear passive peaking EQ.

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Physical modelling sound synthesis is a powerful method for constructing virtual instruments aiming to mimic the sound of realworld counterparts, while allowing for the possibility of engaging with these instruments in ways which may be impossible in person. Such a case is explored in this paper: particularly the simulation of a friction drum inspired instrument. It is an instrument played by causing the membrane of a drum head to vibrate via friction. This involves rubbing the membrane via a stick or a cord attached to its center, with the induced vibrations being transferred to the air inside a sound box. This paper describes the development of a real-time audio application which models such an instrument as a bowed membrane connected to an acoustic tube. This is done by means of a numerical simulation using finite-difference time-domain (FDTD) methods in which the excitation, whose position is free to change in real-time, is modelled by a highly non-linear elasto-plastic friction model. Additionally, the virtual instrument allows for dynamically modifying physical parameters of the model, thereby allowing the user to generate new and interesting sounds that go beyond a realworld friction drum.

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The recently proposed antiderivative antialiasing (ADAA) technique for stateful systems involves two key features: 1) replacing a nonlinearity in a physical model or virtual analog simulation with an antialiased nonlinear system involving antiderivatives of the nonlinearity and time delays and 2) introducing a digital filter in cascade with each original delay in the system. Both of these features introduce the same delay, which is compensated by adjusting the sampling period. The result is a simulation with reduced aliasing distortion. In this paper, we study ADAA using equivalent circuits, answering the question: “Which electrical circuit, discretized using the bilinear transform, yields the ADAA system?” This gives us a new way of looking at the stability of ADAA and how introducing extra filtering distorts a system’s response. We focus on the Wave Digital Filter (WDF) version of this technique.

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Air absorption effects lead to significant attenuation in high frequencies over long distances and this is critical to model in wide-band virtual acoustic simulations. Air absorption is commonly modelled using filter banks applied to an impulse response or to individual impulse events (rays or image sources) arriving at a receiver. Such filter banks require non-trivial fitting to air absorption attenuation curves, as a function of time or distance, in the case of IIR approximations, or may suffer from overlap-add artefacts in the case of FIR approximations. In this study, a filter method is presented which avoids the aforementioned issues. The proposed approach relies on a time-varying diffusion kernel that is found in an approximate Green’s function solution to Stokes’ equation in free space. This kernel acts as a low-pass filter that is parametrised by physical constants, and can be applied to an impulse response using time-varying convolution. Numerical examples are presented demonstrating the utility of this approach for adding air absorption effects to room impulse responses simulated using geometrical acoustics or wave-based methods.

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Live music performances and music production often involve the manipulation of several parameters during sound generation, processing, and mixing. In hardware layouts, those parameters are usually controlled using knobs, sliders and buttons. When these layouts are virtualized, the use of physical (e.g. MIDI) controllers can make interaction easier and reduce the cognitive load associated to sound manipulation. The addition of haptic feedback can further improve such interaction by facilitating the detection of the nature (continuous / discrete) and value of a parameter. To this end, we have realized an endless-knob controller prototype with programmable resistance to rotation, able to render various haptic effects. Ten subjects assessed the effectiveness of the provided haptic feedback in a target-matching task where either visual-only or visual-haptic feedback was provided; the experiment reported significantly lower errors in presence of haptic feedback. Finally, the knob was configured as a multi-parametric controller for a real-time audio effect software written in Python, simulating the voltage-controlled filter aboard the EMS VCS3. The integration of the sound algorithm and the haptic knob is discussed, together with various haptic feedback effects in response to control actions.

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Component-wise circuit modeling, also known as “white-box” modeling, is a well established and much discussed technique in virtual analog modeling. This approach is generally limited in accuracy by lack of access to the exact component values present in a real example of the circuit. In this paper we show how this problem can be addressed by implementing the white-box model in a differentiable form, and allowing approximate component values to be learned from raw input–output audio measured from a real device.

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This paper presents an application of the port Hamiltonian formalism to the nonlinear simulation of the OTA-based Korg35 filter circuit and the Moog 4-pole ladder filter circuit. Lyapunov analysis is used with their state-space representations to guarantee zero-input stability over the range of parameters consistent with the actual circuits. A zero-input stable non-iterative discrete-time scheme based on a discrete gradient and a change of state variables is shown along with numerical simulations. Simulations show behavior consistent with the actual operation of the circuits, e.g., self-oscillation, and are found to be stable and have lower computational cost compared to iterative methods.

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