Figure 1: Our wave coding transforms 7D pressure fields (dependent on source/listener location and time) generated by numerical wave simulation to timeinvariant 6D fields based on four perceptual parameters. Consistent with everyday experience, these parameters vary smoothly in space, aiding compression. Scene geometry ('Deck') is shown on the left, followed by a 2D slice of the parameter fields for a single source (blue dot). Direct sound loudness (L DS ) exhibits strong shadowing while early reflection loudness (L ER ) captures numerous scattered/diffracted paths, and consequently shadows less. Low L DS combined with high L ER conveys a distant and/or occluded source. Early decay time (T ER ) and late reverberation time (T LR ) together indicate scene size, reflectivity and openness. T LR is spatially smoother than T ER , being determined by many more weaker and higher-order paths in this complex space.
AbstractThe acoustic wave field in a complex scene is a chaotic 7D function of time and the positions of source and listener, making it difficult to compress and interpolate. This hampers precomputed approaches which tabulate impulse responses (IRs) to allow immersive, real-time sound propagation in static scenes. We code the field of time-varying IRs in terms of a few perceptual parameters derived from the IR's energy decay. The resulting parameter fields are spatially smooth and compressed using a lossless scheme similar to PNG. We show that this encoding removes two of the seven dimensions, making it possible to handle large scenes such as entire game maps within 100MB of memory. Run-time decoding is fast, taking 100µs per source. We introduce an efficient and scalable method for convolutionally rendering acoustic parameters that generates artifact-free audio even for fast motion and sudden changes in reverberance. We demonstrate convincing spatially-varying effects in complex scenes including occlusion/obstruction and reverberation, in our system integrated with Unreal Engine 3 TM .