Paper Archive

In this paper we extract various timbral attributes for a variety of Irish tin whistles, and use these attributes to form an objective quality assessment of the instruments. This assessment is compared with the subjective experiences of a number of professional musicians. The timbral attributes are drawn from those developed in the Timbre Model [1].

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Iterative solvers are required for the discrete-time simulation of nonlinear behaviour in analogue distortion circuits. Unfortunately, these methods are often computationally too expensive for realtime simulation. Two methods are presented which attempt to reduce the expense of iterative solvers. This is achieved by applying information that is derived from the specific form of the nonlinearity. The approach is first explained through the modelling of an asymmetrical diode clipper, and further exemplified by application to the Dallas Rangemaster Treble Booster guitar pedal, which provides an initial perspective of the performance on systems with multiple nonlinearities.

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Most real systems, from acoustics to analog electronics, are characterised by bidirectional coupling amongst elements rather than neat, unidirectional signal flows between self-contained modules. Integrating digital processing into physical domains becomes a significant engineering challenge when the application requires bidirectional coupling across the physical-digital boundary rather than separate, well-defined inputs and outputs. We introduce an approach to hybrid analog-digital audio processing using synthetic impedance: digitally simulated circuit elements integrated into an otherwise analog circuit. This approach combines the physicality and classic character of analog audio circuits alongside the precision and flexibility of digital signal processing (DSP). Our impedance synthesis system consists of a voltage-controlled current source and a microcontroller-based DSP system. We demonstrate our technique through modifying an iconic guitar distortion pedal, the Boss DS-1, showing the ability of the synthetic impedance to both replicate and extend the behaviour of the pedal’s diode clipping stage. We discuss the behaviour of the synthetic impedance in isolated laboratory conditions and in the DS-1 pedal, highlighting the technical and creative potential of the technique as well as its practical limitations and future extensions.

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Solitons are special solutions of certain nonlinear partial differential equations of mathematical physics. They exhibit properties that are partly similar to the solutions of the linear wave equation and partly similar to the behaviour of colliding particles. Their characteristic features are well-known in the mathematical literature but few closed-form solutions are available. This contribution derives algorithmic structures for the computation of solitons in a dimensionless space-time domain which can be scaled to the audio frequency range. The investigations are confined to first and second order solutions of the Korteweg-de Vries equation. Sound examples show that the effects of wave propagation and soliton interaction can be represented by audible events.

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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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This paper introduces a computationally efficient method for the emulation of nonlinear analog audio circuits by combining state-space representations, constraint stabilization, and convex quadratic programming (QP). Unlike traditional virtual analog (VA) modeling approaches or computationally demanding SPICE-based simulations, our approach reformulates the nonlinear differential-algebraic (DAE) systems that arise from analog circuit analysis into numerically stable optimization problems. The proposed method efficiently addresses the numerical challenges posed by nonlinear algebraic constraints via constraint stabilization techniques, significantly enhancing robustness and stability, suitable for real-time simulations. A canonical diode clipper circuit is presented as a test case, demonstrating that our method achieves accurate and faster emulations compared to conventional state-space methods. Furthermore, our method performs very well even at substantially lower sampling rates. Preliminary numerical experiments confirm that the proposed approach offers improved numerical stability and real-time feasibility, positioning it as a practical solution for high-fidelity audio applications.

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In the digital simulation of non-linear audio effect circuits, the arising non-linear equation system generally poses the main challenge for a computationally cheap implementation. As the computational complexity grows super-linearly with the number of equations, it is beneficial to decompose the equation system into several smaller systems, if possible. In this paper we therefore develop an approach to determine such a decomposition automatically. We limit ourselves to cases where an exact decomposition is possible, however, and do not consider approximate decompositions.

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This paper presents a digital grey box model of a late 1960s era Shin-ei Uni-Vibe(r) 1 analog effects foot pedal. As an early phase shifter, it achieved wide success in popular music as a unique musical effect, noteworthy for its pulsating and throbbing modulation sounds. The Uni-Vibe is an early series all-pass phaser effect, where each first-order section is a discrete component phase splitter (no operational amplifiers). The dynamic sweeping movement of the effect arises from a single LFO-driven incandescent lamp opto-coupled to the light dependent resistors (LDRs) of each stage. The proposed method combines digital circuit models with measured LDR characteristics for the four phase shift stages of an original Uni-Vibe unit, resulting in an efficient emulation that preserves the character of the Uni-Vibe. In modeling this iconic effect, we also aim to offer some historical and technical insight into the exact nature of its unique sound.

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This paper introduces a new open-source Python library for the modeling and simulation of wave digital filter (WDF) circuits. The library, called pwydf, allows users to easily create and analyze WDF circuit models in a high-level, object-oriented manner. The library includes a variety of built-in components, such as voltage sources, capacitors, diodes etc., as well as the ability to create custom components and circuits. Additionally, pywdf includes a variety of analysis tools, such as frequency response and transient analysis, to aid in the design and optimization of WDF circuits. We demonstrate the library’s efficacy in replicating the nonlinear behavior of an analog diode clipper circuit, and in creating an allpass filter that cannot be realized in the analog world. The library is well-documented and includes several examples to help users get started. Overall, pywdf is a powerful tool for anyone working with WDF circuits, and we hope it can be of great use to researchers and engineers in the field.

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Machine learning approaches to modelling analog audio effects have seen intensive investigation in recent years, particularly in the context of non-linear time-invariant effects such as guitar amplifiers. For modulation effects such as phasers, however, new challenges emerge due to the presence of the low-frequency oscillator which controls the slowly time-varying nature of the effect. Existing approaches have either required foreknowledge of this control signal, or have been non-causal in implementation. This work presents a differentiable digital signal processing approach to modelling phaser effects in which the underlying control signal and time-varying spectral response of the effect are jointly learned. The proposed model processes audio in short frames to implement a time-varying filter in the frequency domain, with a transfer function based on typical analog phaser circuit topology. We show that the model can be trained to emulate an analog reference device, while retaining interpretable and adjustable parameters. The frame duration is an important hyper-parameter of the proposed model, so an investigation was carried out into its effect on model accuracy. The optimal frame length depends on both the rate and transient decay-time of the target effect, but the frame length can be altered at inference time without a significant change in accuracy.

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