A boundary integral formalism for stochastic ray tracing in billiards

Determining the flow of rays or non-interacting particles driven by a force or velocity field is fundamental to modelling many physical processes. These include particle flows arising in fluid mechanics and ray flows arising in the geometrical optics limit of linear wave equations. In many practical applications, the driving field is not known exactly and the dynamics are determined only up to a degree of uncertainty. This paper presents a boundary integral framework for propagating flows including uncertainties, which is shown to systematically interpolate between a deterministic and a completely random description of the trajectory propagation. A simple but efficient discretisation approach is applied to model uncertain billiard dynamics in an integrable rectangular domain

Effects of virtual acoustics on dynamic auditory distance perception

Sound propagation encompasses various acoustic phenomena including reverberation. Current virtual acoustic methods, ranging from parametric filters to physically-accurate solvers, can simulate reverberation with varying degrees of fidelity. We investigate the effects of reverberant sounds generated using different propagation algorithms on acoustic distance perception, i.e., how faraway humans perceive a sound source. In particular, we evaluate two classes of methods for real-time sound propagation in dynamic scenes based on parametric filters and ray tracing. Our study shows that the more accurate method shows less distance compression as compared to the approximate, filter-based method. This suggests that accurate reverberation in VR results in a better reproduction of acoustic distances. We also quantify the levels of distance compression introduced by different propagation methods in a virtual environment.Comment: 8 Pages, 7 figure

Sound propagation in realistic interactive 3D scenes with parameterized sources using deep neural operators

We address the challenge of sound propagation simulations in 3D virtual rooms with moving sources, which have applications in virtual/augmented reality, game audio, and spatial computing. Solutions to the wave equation can describe wave phenomena such as diffraction and interference. However, simulating them using conventional numerical discretization methods with hundreds of source and receiver positions is intractable, making stimulating a sound field with moving sources impractical. To overcome this limitation, we propose using deep operator networks to approximate linear wave-equation operators. This enables the rapid prediction of sound propagation in realistic 3D acoustic scenes with moving sources, achieving millisecond-scale computations. By learning a compact surrogate model, we avoid the offline calculation and storage of impulse responses for all relevant source/listener pairs. Our experiments, including various complex scene geometries, show good agreement with reference solutions, with root mean squared errors ranging from 0.02 Pa to 0.10 Pa. Notably, our method signifies a paradigm shift as no prior machine learning approach has achieved precise predictions of complete wave fields within realistic domains. We anticipate that our findings will drive further exploration of deep neural operator methods, advancing research in immersive user experiences within virtual environments.$Comment: 25 pages, 10 figures, 4 table

Interactive Sound Propagation using Precomputation and Statistical Approximations

Acoustic phenomena such as early reflections, diffraction, and reverberation have been shown to improve the user experience in interactive virtual environments and video games. These effects arise due to repeated interactions between sound waves and objects in the environment. In interactive applications, these effects must be simulated within a prescribed time budget. We present two complementary approaches for computing such acoustic effects in real time, with plausible variation in the sound field throughout the scene. The first approach, Precomputed Acoustic Radiance Transfer, precomputes a matrix that accounts for multiple acoustic interactions between all scene objects. The matrix is used at run time to provide sound propagation effects that vary smoothly as sources and listeners move. The second approach couples two techniques -- Ambient Reverberance, and Aural Proxies -- to provide approximate sound propagation effects in real time, based on only the portion of the environment immediately visible to the listener. These approaches lie at different ends of a space of interactive sound propagation techniques for modeling sound propagation effects in interactive applications. The first approach emphasizes accuracy by modeling acoustic interactions between all parts of the scene; the second approach emphasizes efficiency by only taking the local environment of the listener into account. These methods have been used to efficiently generate acoustic walkthroughs of architectural models. They have also been integrated into a modern game engine, and can enable realistic, interactive sound propagation on commodity desktop PCs.Doctor of Philosoph

Perceptually Driven Interactive Sound Propagation for Virtual Environments

Sound simulation and rendering can significantly augment a user‘s sense of presence in virtual environments. Many techniques for sound propagation have been proposed that predict the behavior of sound as it interacts with the environment and is received by the user. At a broad level, the propagation algorithms can be classified into reverberation filters, geometric methods, and wave-based methods. In practice, heuristic methods based on reverberation filters are simple to implement and have a low computational overhead, while wave-based algorithms are limited to static scenes and involve extensive precomputation. However, relatively little work has been done on the psychoacoustic characterization of different propagation algorithms, and evaluating the relationship between scientific accuracy and perceptual benefits.In this dissertation, we present perceptual evaluations of sound propagation methods and their ability to model complex acoustic effects for virtual environments. Our results indicate that scientifically accurate methods for reverberation and diffraction do result in increased perceptual differentiation. Based on these evaluations, we present two novel hybrid sound propagation methods that combine the accuracy of wave-based methods with the speed of geometric methods for interactive sound propagation in dynamic scenes.Our first algorithm couples modal sound synthesis with geometric sound propagation using wave-based sound radiation to perform mode-aware sound propagation. We introduce diffraction kernels of rigid objects,which encapsulate the sound diffraction behaviors of individual objects in the free space and are then used to simulate plausible diffraction effects using an interactive path tracing algorithm. Finally, we present a novel perceptual driven metric that can be used to accelerate the computation of late reverberation to enable plausible simulation of reverberation with a low runtime overhead. We highlight the benefits of our novel propagation algorithms in different scenarios.Doctor of Philosoph

Efficient Acoustic Simulation for Immersive Media and Digital Fabrication

Sound is a crucial part of our life. Well-designed acoustic behaviors can lead to significant improvement in both physical and virtual interactions. In computer graphics, most existing methods focused primarily on improving the accuracy. It remained underexplored on how to develop efficient acoustic simulation algorithms for interactive practical applications. The challenges arise from the dilemma between expensive accurate simulations and fast feedback demanded by intuitive user interaction: traditional physics-based acoustic simulations are computationally expensive; yet, for end users to benefit from the simulations, it is crucial to give prompt feedback during interactions. In this thesis, I investigate how to develop efficient acoustic simulations for real-world applications such as immersive media and digital fabrication. To address the above-mentioned challenges, I leverage precomputation and optimization to significantly improve the speed while preserving the accuracy of complex acoustic phenomena. This work discusses three efforts along this research direction: First, to ease sound designer's workflow, we developed a fast keypoint-based precomputation algorithm to enable interactive acoustic transfer values in virtual sound simulations. Second, for realistic audio editing in 360° videos, we proposed an inverse material optimization based on fast sound simulation and a hybrid ambisonic audio synthesis that exploits the directional isotropy in spatial audios. Third, we devised a modular approach to efficiently simulate and optimize fabrication-ready acoustic filters, achieving orders of magnitudes speedup while maintaining the simulation accuracy. Through this series of projects, I demonstrate a wide range of applications made possible by efficient acoustic simulations

A framework for auralization of boundary element method simulations including source and receiver directivity

The Boundary Element Method (BEM) is a proven numerical prediction tool for computation of room acoustic transfer functions, as are required for auralization of a virtual space. In this paper it is validated against case studies drawn from the ‘Ground Truth for Room Acoustical Simulation’ database within a framework that includes source and receiver directivity. These aspects are often neglected but are respectively important to include for auralization applications because source directivity is known to affect how a room is excited and because the human auditory system is sensitive to directional cues. The framework uses weighted-sums of spherical harmonic functions to represent both the source directivity to be simulated and the pressure field predicted in the vicinity of the receiver location, the coefficients of the former being fitted to measured directivity and those of the latter computed directly from the boundary data by evaluating a boundary integral. Three validation cases are presented, one of which includes a binaural receiver. The computed results match measurements closely for the two cases conducted in anechoic conditions but show some significant differences for the third room scenario; here it is likely that uncertainty in boundary material data limited modelling accuracy