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Distance Modeling
HRTFs help us identify a sound’s direction, but they do not model our localization of distance. Humans use several factors to infer the distance to a sound source. These can be simulated with varying degrees of accuracy and cost in software:
-Loudness, our most reliable cue, is trivial to model with simple attenuation based on distance between the source and the listener.
-Initial Time Delay is significantly harder to model, as it requires computing the early reflections for a given set of geometry, along with that geometry’s characteristics. This is both computationally expensive and awkward to implement architecturally (specifically, sending world geometry to a lower level API is often complex). Even so, several packages have made attempts at this, ranging from simple “shoebox models” to elaborate full scene geometric modeling.
-Direct vs. Reverberant Sound (or, in audio production, the “wet/dry mix”) is a natural byproduct of any system that attempts to accurately model reflections and late reverberations. Unfortunately, such systems tend to be very expensive computationally. With ad hoc models based on artificial reverberators, the mix setting can be adjusted in software, but these are strictly empirical models.
-Motion Parallax we get “for free,” because it is a byproduct of the velocity of a sound source.
-High Frequency Attenuation due to air absorption is a minor effect, but it is also reasonably easy to model by applying a simple low-pass filter, and by adjusting cutoff frequency and slope. In practice, HF attenuation is not very significant in comparison to the other distance cues.