Download Non-Iterative Numerical Simulation in Virtual Analog: A Framework Incorporating Current Trends For their low and constant computational cost, non-iterative methods for the solution of differential problems are gaining popularity
in virtual analog provided their stability properties and accuracy
level afford their use at no exaggerate temporal oversampling. At
least in some application case studies, one recent family of noniterative schemes has shown promise to outperform methods that
achieve accurate results at the cost of iterating several times while
converging to the numerical solution. Here, this family is contextualized and studied against known classes of non-iterative methods.
The results from these studies foster a more general discussion
about the possibilities, role and prospective use of non-iterative
methods in virtual analog.
Download Revisiting the Second-Order Accurate Non-Iterative Discretization Scheme In the field of virtual analog modeling, a variety of methods have been proposed to systematically derive simulation models from circuit schematics. However, they typically rely on implicit numerical methods to transform the differential equations governing the circuit to difference equations suitable for simulation. For circuits with non-linear elements, this usually means that a non-linear equation has to be solved at run-time at high computational cost. As an alternative to fully-implicit numerical methods, a family of non-iterative discretization schemes has recently been proposed, allowing a significant reduction of the computational load. However, in the original presentation, several assumptions are made regarding the structure of the ODE, limiting the generality of these schemes. Here, we show that for the second-order accurate variant in particular, the method is applicable to general ODEs. Furthermore, we point out an interesting connection to the implicit midpoint method.
Download Directivity Patterns Controlling the Auditory Source Distance What influence does the directivity of a sound source have on the perceived distance impression in a room? We propose different directivity pattern designs able to modify the auditory source distance. The idea is accompanied with a comprehensive experimental study investigating the audio effect and its behavior by auralization of directional sound source and room using a 24-channel loudspeaker ring inside an anechoic chamber. In addition to the proposed directivity designs, the study covers influence of auralized room, source-to-receiver distance, signal, and single-channel reverberation. Moreover, simple room acoustical measures perform well in predicting the new effect.
Download Differentiable grey-box modelling of phaser effects using frame-based spectral processing 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.
Download Group Delay-Based Allpass Filters for Abstract Sound Synthesis and Audio Effects Processing An algorithm for artistic spectral audio processing and synthesis using allpass filters is presented. These filters express group delay trajectories, allowing fine control of their frequency-dependent arrival times. We present methods for designing the group delay trajectories to yield a novel class of filters for sound synthesis and audio effects processing. A number of categories of group delay trajectory design are discussed, including stair-stepped, modulated, and probabilistic. Synthesis and processing examples are provided.
Download Transaural 3-D audio with user-controlled calibration A calibration method allowing users to customize the loudspeaker layout for 2-, 4-, and 5.1-channel playback, and to steer the “sweet spot” to the position o f the listener’s head is presented. The method, which is applied to a computationally efficient transaural 3D audio system for dynamic spatialization o f multiple sound sources, is based on u ser interaction and auditory feedback. The robustness of the a uditory sensation is analyzed for small displacements of the listener near the sweet spot. A modification of the system permits continuous adjustment of the sweet spot size by the listener. The modification limits the a rtifacts due to the transaural processing for positions away from the sweet spot. For wide settings, the system gradually reduces to a discrete amplitude panning system.
Download More Modal Fun - “Forced Vibration” at One Point The question, if a vibrating object can be forced to follow a given movement profile at one point forms a case of an inverse problem. It is shown that for the specific setting of an object described by modal data, this question may be solved by a newly developed method. The new technique has several strengths, such as allowing to compute modal data for the constrained scenario and forming a basis for precise and stable simulations. The latter potential is shown at a short example, a stiff string being hammered against a fixed board by a hammer of infinite mass.
Download Digital Filtering for Musicians The CD-ROM Digital Filtering for Musicians was made to build a bridge between two very diverse, yet interrelated topics; digital audio techniques and music, with the main focus on one of the central techniques: filtering. To make optimal use of digital filtering in a musical context requires insight in mathematics and computational theory as well as music. By presenting these three fields side-by-side on an interactive basis, readers can familiarize themselves with the relevant topics and their relations, without being overwhelmed by the complexity of the subject.
Download Efficient Simulation of the Bowed String in Modal Form The motion of a bowed string is a typical nonlinear phenomenon resulting from a friction force via interaction with the bow. The system can be described using suitable differential equations. Implicit numerical discretisation methods are known to yield energy consistent algorithms, essential to ensure stability of the timestepping schemes. However, reliance on iterative nonlinear root finders carries significant implementation issues. This paper explores a method recently developed which allows nonlinear systems of ordinary differential equations to be solved non-iteratively. Case studies of a mass-spring system and an ideal string coupled with a bow are investigated. Finally, a stiff string with loss is also considered. Combining semi-discretisation and a modal approach results in an algorithm yielding faster than real-time simulation of typical musical strings.
Download Evaluating Neural Networks Architectures for Spring Reverb Modelling Reverberation is a key element in spatial audio perception, historically achieved with the use of analogue devices, such as plate and spring reverb, and in the last decades with digital signal processing techniques that have allowed different approaches for Virtual Analogue Modelling (VAM). The electromechanical functioning of the spring reverb makes it a nonlinear system that is difficult to fully emulate in the digital domain with white-box modelling techniques. In this study, we compare five different neural network architectures, including convolutional and recurrent models, to assess their effectiveness in replicating the characteristics of this audio effect. The evaluation is conducted on two datasets at sampling rates of 16 kHz and 48 kHz. This paper specifically focuses on neural audio architectures that offer parametric control, aiming to advance the boundaries of current black-box modelling techniques in the domain of spring reverberation.