Eigenmode compression for modal sound models

Abstract

We propose and evaluate a method for significantly compressing modal sound models, thereby making them far more practical for audiovisual applications. The dense eigenmode matrix, needed to compute the sound model's response to contact forces, can consume tens to thousands of megabytes depending on mesh resolution and mode count. Our eigenmode compression pipeline is based on nonlinear optimization of Moving Least Squares (MLS) approximations. Enhanced compression is achieved by exploiting symmetry both within and between eigenmodes, and by adaptively assigning per-mode error levels based on human perception of the far-field pressure amplitudes. Our method provides smooth eigenmode approximations, and efficient random access. We demonstrate that, in many cases, hundredfold compression ratios can be achieved without audible degradation of the rendered sound.

Creating Real-Time Aeroacoustic Sound Effects Using Physically Informed Models

“…In contrast, it can be argued that participants will have more likely heard the actual sounds of a golf club or baseball bat at live sporting events or within sporting broadcasts and hence their memory of these sounds would be closer to the physical model. It would be of interest to carry out the perceptual evaluation with the sound effects played in context with an animation, similar to those presented in [21,22]. In recent listening tests participants indicated that a combined audiovisual stimulus would be preferred over audio on its own.…”

“…Finite element analysis is one method for computing the vibration modes. Modal synthesis for musical instruments is described in [20], which can be extended to contact forces [21] and bubble/water sounds [22].…”

Compressed vibration modes of elastic bodies

“…One drawback of using vibration modes for dimensional reduction is that the resulting basis vectors are dense, which can be problematic when a large basis is used or applications, like games, impose strict limits on the memory available for the reduced simulation. This problem has been addressed in [19] by applying a data compression scheme for storing the basis vectors. We present, for the first time, a localization of vibration modes, which allows for creating bases of low-energy deformations that are sparse.…”

Aerophones in flatland

“…Over the last decade sound synthesis has received increasing attention, such as the sound of water [Zheng and James 2009] and fire [Chadwick and James 2011]. Rigid body sounds have attracted considerable interest in particular, especially using precomputed modal analysis [O'Brien et al 2002;Chadwick et al 2009;Chadwick et al 2012;Langlois et al 2014]. Auralizing physical events such as objects breaking, rolling and sliding in synchronization with visual cues aids immersion in virtual environments.…”