Download Sound Modeling from the Analysis of Real Sounds This work addresses sound modeling using a combination of physical and signal models with a particular emphasis on the flute sound. For that purpose, analysis methods adapted to the nonstationary nature of sounds are developed. Further on parameters characterizing the sound from a perceptive and a physical point of view are extracted. The synthesis process is then designed to reproduce a perceptive effect and to simulate the physical behavior of the sound generating system. The correspondence between analysis and synthesis parameters is crucial and can be achieved using both mathematical and perceptive criteria. Real-time control of such models makes it possible to use specially designed interfaces mirroring already existing sound generators like traditional musical instruments.
Download Simplified, Physically-Informed Models of Distortion and Overdrive Guitar Effects Pedals This paper explores a computationally efficient, physically informed approach to design algorithms for emulating guitar distortion circuits. Two iconic effects pedals are studied: the “Distortion” pedal and the “Tube Screamer” or “Overdrive” pedal. The primary distortion mechanism in both pedals is a diode clipper with an embedded low-pass filter, and is shown to follow a nonlinear ordinary differential equation whose solution is computationally expensive for real-time use. In the proposed method, a simplified model, comprising the cascade of a conditioning filter, memoryless nonlinearity and equalization filter, is chosen for its computationally efficient, numerically robust properties. Often, the design of distortion algorithms involves tuning the parameters of this filter-distortion-filter model by ear to match the sound of a prototype circuit. Here, the filter transfer functions and memoryless nonlinearities are derived by analysis of the prototype circuit. Comparisons of the resulting algorithms to actual pedals show good agreement and demonstrate that the efficient algorithms presented reproduce the general character of the modeled pedals.
Download Large-scale Real-time Modular Physical Modeling Sound Synthesis Due to recent increases in computational power, physical modeling synthesis is now possible in real time even for relatively complex models. We present here a modular physical modeling instrument design, intended as a construction framework for string- and bar- based instruments, alongside a mechanical network allowing for arbitrary nonlinear interconnection. When multiple nonlinearities are present in a feedback setting, there are two major concerns. One is ensuring numerical stability, which can be approached using an energy-based framework. The other is coping with the computational cost associated with nonlinear solvers—standard iterative methods, such as Newton-Raphson, quickly become a computational bottleneck. Here, such iterative methods are sidestepped using an alternative energy conserving method, allowing for great reduction in computational expense or, alternatively, to real-time performance for very large-scale nonlinear physical modeling synthesis. Simulation and benchmarking results are presented.
Download A Physical Model of the Trombone Using Dynamic Grids for Finite-Difference Schemes 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.
Download Physical Modeling Using Recurrent Neural Networks with Fast Convolutional Layers Discrete-time modeling of acoustic, mechanical and electrical systems is a prominent topic in the musical signal processing literature. Such models are mostly derived by discretizing a mathematical model, given in terms of ordinary or partial differential equations, using established techniques. Recent work has applied the techniques of machine-learning to construct such models automatically from data for the case of systems which have lumped states described by scalar values, such as electrical circuits. In this work, we examine how similar techniques are able to construct models of systems which have spatially distributed rather than lumped states. We describe several novel recurrent neural network structures, and show how they can be thought of as an extension of modal techniques. As a proof of concept, we generate synthetic data for three physical systems and show that the proposed network structures can be trained with this data to reproduce the behavior of these systems.
Download A new estimation technique for determining the control parameters of a physical model of a trumpet A new estimation technique is proposed which computes the control parameters of a physical model of a trumpet in order to simulate a recording of a real instrument. First, the physical constraints of the instrument and the prior knowledge about how a player controls a trumpet are described. This is taken into account during the design of the data set and guarantees that these constraints are respected. Then, an estimation procedure minimizes two perceptual similarity criteria in function of the control parameters. The first criterium expresses the difference of the spectral envelopes and the second one the difference in fundamental frequency. An optimization technique is proposed that yields an optimal solution for the fundamental frequency, and a conditional suboptimal solution for the spectral envelope. A robust implementation of the technique was developed for which it is shown that the estimated parameters are unique and that the optimization does not suffer from local minima.
Download Automatic synthesis strategies for object-based dynamical physical models in musical acoustics Current physics-based synthesis techniques tend to synthesize the interaction between different functional elements of a sound generator by treating it as a single system. However, when dealing with the physical modeling of complex sound generators this choice raises questions about the resulting flexibility of the adopted synthesis strategy. One way to overcome this problem is to approach it by individually synthesizing and discretizing the objects that contribute to the generation of sounds. In this paper we address the problem of how to automatize the process of physically modeling the interaction between objects, and how to make it dynamical. We will show that this can be done through the automatic definition and implementation of a topology model that adapts to the contact and proximity conditions between the considered objects.
Download A Power-Balanced Dynamic Model of Ferromagnetic Coils This paper proposes a new macroscopic physical model of ferromagnetic coils used in audio circuits. To account for realistic
saturation and hysteretic phenomena, this model combines statistical physics results, measurement-driven refinements and portHamiltonian formulations that guarantee passivity, thermodynamic
consistency and composability according to both electric and thermal ports. As an illustration, the model is used to simulate a passive high-pass filter. Different types of audio inputs are considered
and simulations are compared to measurements.
Download Adjustable Boundary Conditions for Multidimensional Transfer Function Models Block based physical modeling requires to provide a library of modeling blocks for standard components of real or virtual musical instruments. Complex synthesis models are built by connecting standard components in a physically meaningful way. These connections are investigated for modeling a resonating structure as a distributed parameter system. The dependence of a resonator’s spectral structure on the termination of its ports is analyzed. It is shown that the boundary conditions of a distributed parameter system can be adjusted by proper termination only. Examples show the corresponding variation of the resonator’s spectral structure in response to variations of the external termination.
Download Physically Based Sound Synthesis and Control of Footsteps Sounds We describe a system to synthesize in real-time footsteps sounds. The sound engine is based on physical models and physically inspired models reproducing the act of walking on several surfaces. To control the real-time engine, three solutions are proposed. The first two solutions are based on floor microphones, while the third one is based on shoes enhanced with sensors. The different solutions proposed are discussed in the paper.