Download Reverberation still in business: Thickening and Propagating micro-textures in physics-based sound modeling Artificial reverberation is usually introduced, as a digital audio effect, to give a sense of enclosing architectural space. In this paper we argue about the effectiveness and usefulness of diffusive reverberators in physically-inspired sound synthesis. Examples are given for the synthesis of textural sounds, as they emerge from solid mechanical interactions, as well as from aerodynamic and liquid phenomena.
Download Learning Nonlinear Dynamics in Physical Modelling Synthesis Using Neural Ordinary Differential Equations Modal synthesis methods are a long-standing approach for modelling distributed musical systems. In some cases extensions are
possible in order to handle geometric nonlinearities. One such
case is the high-amplitude vibration of a string, where geometric nonlinear effects lead to perceptually important effects including pitch glides and a dependence of brightness on striking amplitude. A modal decomposition leads to a coupled nonlinear system of ordinary differential equations. Recent work in applied machine learning approaches (in particular neural ordinary differential equations) has been used to model lumped dynamic systems
such as electronic circuits automatically from data. In this work,
we examine how modal decomposition can be combined with neural ordinary differential equations for modelling distributed musical systems. The proposed model leverages the analytical solution
for linear vibration of system’s modes and employs a neural network to account for nonlinear dynamic behaviour. Physical parameters of a system remain easily accessible after the training without
the need for a parameter encoder in the network architecture. As
an initial proof of concept, we generate synthetic data for a nonlinear transverse string and show that the model can be trained to
reproduce the nonlinear dynamics of the system. Sound examples
are presented.
Download Parametric Audio Coding of Bass Guitar Recordings Using a Tuned Physical Modeling Algorithm In this paper, we propose a parametric audio coding framework that combines the analysis and re-synthesis of electric bass guitar recordings. In particular, an existing synthesis algorithm that incorporates 11 playing techniques is extended by two calibration algorithms. Both the temporal and spectral decay parameters as well as the inharmonicity coefficient are set according to the fretboard position on the instrument. Listening tests show that there is still a gap in perceptual quality between real-world instrument recordings and the re-synthesized versions. Due to this gap, the perceived improvement due to the model calibration is only small. Second, the listening tests reveal that the plucking styles are more important towards realistic synthesis results than expression styles.
Download Controlling a Non Linear Friction Model for Evocative Sound Synthesis Applications In this paper, a flexible strategy to control a synthesis model of sounds produced by non linear friction phenomena is proposed for guidance or musical purposes. It enables to synthesize different types of sounds, such a creaky door, a singing glass or a squeaking wet plate. This approach is based on the action/object paradigm that enables to propose a synthesis strategy using classical linear filtering techniques (source/resonance approach) which provide an efficient implementation. Within this paradigm, a sound can be considered as the result of an action (e.g. impacting, rubbing, ...) on an object (plate, bowl, ...). However, in the case of non linear friction phenomena, simulating the physical coupling between the action and the object with a completely decoupled source/resonance model is a real and relevant challenge. To meet this challenge, we propose to use a synthesis model of the source that is tuned on recorded sounds according to physical and spectral observations. This model enables to synthesize many types of non linear behaviors. A control strategy of the model is then proposed by defining a flexible physically informed mapping between a descriptor, and the non linear synthesis behavior. Finally, potential applications to the remediation of motor diseases are presented. In all sections, video and audio materials are available at the following URL: http://www.lma.cnrs-mrs.fr/~kronland/ thoretDAFx2013/
Download Timpani Drum Synthesis in 3D on GPGPUs Physical modeling sound synthesis for systems in 3D is a computationally intensive undertaking; the number of degrees of freedom is very large, even for systems and spaces of modest physical dimensions. The recent emergence into the mainstream of highly parallel multicore hardware, such as general purpose graphical processing units (GPGPUs) has opened an avenue of approach to synthesis for such systems in a reasonable amount of time, without severe model simplification. In this context, new programming and algorithm design considerations appear, especially the ease with which a given algorithm may be parallelized. To this end finite difference time domain methods operating over regular grids are explored, with regard to an interesting and non-trivial test problem, that of the timpani drum. The timpani is chosen here because its sounding mechanism relies on the coupling between a 2D resonator and a 3D acoustic space (an internal cavity). It is also of large physical dimensions, and thus simulation is of high computational cost. A timpani model is presented, followed by a brief presentation of finite difference time domain methods, followed by a discussion of parallelization on GPGPU, and simulation results.
Download Sonification of the Fission Model as an Event Generation System I am proposing an event generation system for sonification purposes, where a simplified chain reaction model known as nuclear fission in physics is used. The basic background of the fission model, mapping of parameters as sonic entities and technical aspects of the realization procedure are presented.
Download Modeling Interactions between Rubbed Dry Surfaces Using an Elasto-Plastic Friction Model A physically based model of the frictional interaction between dry surfaces is presented. The paper reviews a number of static and dynamic friction models, and discusses numerical techniques for the accurate and efficient numerical implementation of a dynamic elasto-plastic model. An application to the bowed string is provided, and the resulting simulations are compared to recent results from the literature.
Download Object-Based Synthesis of Scraping and Rolling Sounds Based on Non-Linear Physical Constraints 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.
Download A Physically-Informed, Circuit-Bendable, Digital Model of the Roland TR-808 Bass Drum Circuit We present an analysis of the bass drum circuit from the classic Roland TR-808 Rhythm Composer, based on physical models of the device’s many sub-circuits. A digital model based on this analysis (implemented in Cycling 74’s Gen˜) retains the salient features of the original and allows accurate emulation of circuit-bent modifications—complicated behavior that is impossible to capture through black-box modeling or structured sampling. Additionally, this analysis will clear up common misconceptions about the circuit, support the design of further drum machine modifications, and form a foundation for circuit-based musicological inquiry into the history of analog drum machines.
Download Physical Model Parameter Optimisation for Calibrated Emulation of the Dallas Rangemaster Treble Booster Guitar Pedal In this work we explore optimising parameters of a physical circuit model relative to input/output measurements, using the Dallas Rangemaster Treble Booster as a case study. A hybrid metaheuristic/gradient descent algorithm is implemented, where the initial parameter sets for the optimisation are informed by nominal values from schematics and datasheets. Sensitivity analysis is used to screen parameters, which informs a study of the optimisation algorithm against model complexity by fixing parameters. The results of the optimisation show a significant increase in the accuracy of model behaviour, but also highlight several key issues regarding the recovery of parameters.