Listener-based Analysis of Surface Importance for Acoustic Metrics

Abstract

Acoustic quality in room acoustics is measured by well defined quantities, like definition, which can be derived from simulated impulse response filters or measured values. These take into account the intensity and phase shift of multiple reflections due to a wave front emanating from a sound source. Definition (D50) and clarity (C50) for example correspond to the fraction of the energy received in total to the energy received in the first 50 ms at a certain listener position. Unfortunately, the impulse response measured at a single point does not provide any information about the direction of reflections, and about the reflection surfaces which contribute to this measure. For the visualization of room acoustics, however, this information is very useful since it allows to discover regions with high contribution and provides insight into the influence of all reflecting surfaces to the quality measure. We use the phonon tracing method to calculate the contribution of the reflection surfaces to the impulse response for different listener positions. This data is used to compute importance values for the geometry taking a certain acoustic metric into account. To get a visual insight into the directional aspect, we map the importance to the reflecting surfaces of the geometry. This visualization indicates which parts of the surfaces need to be changed to enhance the chosen acoustic quality measure. We apply our method to the acoustic improvement of a lecture hall by means of enhancing the overall speech comprehensibility (clarity) and evaluate the results using glyphs to visualize the clarity (C50) values at listener positions throughout the room.

Visualization for the Physical Sciences

“…Multi‐field 2D data is visualized using a field [LFH08] or using time [YXG*10] as a third dimension. Multi‐field 3D data is visualized using glyphs and a variation in the glyph colour [SIG05] or shape [CFG*05, BvL06, JKM06, DMB*06, MDHB*07], using trajectories, vector glyphs or surfaces together with volume rendering [SYS*06, JCSB03], parallel coordinates [QCX*07] or multiple‐linked views and brushing [CFG*05, KLM*08].…”

“…We review papers that simulate sound within a room [BDM*05, LCM07b, CLT*08, BMD*08], that show how the material on room surfaces influences sound [DMB*06, MDHB*07], and present a comparative visualization of two different approaches for acoustic simulation [DBM*06].…”

AD-Frustum: Adaptive Frustum Tracing for Interactive Sound Propagation

“…Ray-based or Particle-based Techniques: Some of the earliest methods for geometric sound propagation are based on tracing sampled-rays [16] or sound-particles (phonons) [14,2,6,23] from a source to the listener. Recent improvements, including optimized hierarchies and exploiting ray-coherence, make it possible for ray-based and particle-based methods to handle complex, dynamic scenes on commodity hardware [39] or handle massive models [20].…”

Sound Tracing: Rendering Listener Specific Acoustic Room Properties

“…Additionally we visualized the results at a listener position using a color coded sphere which is deformed according to the direction and amount of the received energy. In [MDHB + 07] we introduced a visual analysis approach of acoustic quality at listener positions utilizing acoustic parameters (metrics) and gave an example of improvement of speech comprehensibility inside a lecture room.…”