I am fascinated by the effect of air on sound. In particular, I’m interested in the effect it has on the sound of air and road traffic. It sounds like a ‘tumbling’ or ‘folding’ of sound, with fluctuations in loudness, direction, and filtered frequencies. Here is an example of the effect in a recording of F15e fighter aircraft dogfighting in Lakenheath, Norfolk, by Microscopia, available at The Freesound Project:
I hope to reproduce the effect by analysing it and understanding its components. This post represents my intial thoughts on the subject and some ideas on how it might work. The aim is to develop my understanding of the environmental acoustic phenomenon, and – if the effect can be modelled – use it as a tool for processing sound.
Let’s try to identify the components of the sound effect of air, beginning with some basic observations. We mainly find this effect in the sound of distant air and road traffic, but it also happens with other loud, broad-spectrum sounds heard at a distance, such as a massed crowd or fireworks, though the latter are so short that the effect is less apparent. Presumably it also affects quieter sounds, but those we cannot hear. It seems fair to assume that its intensity is porportional to distance; the farther away we hear a sound, the greater is the perceived effect. In this sense, we might say that it is a sonic equivalent to ‘aerial (or atmospheric) perspective’ – the blue-tinged haze that reduces contrast and colour in a distant skyline. Fog is a more intense version of the same thing. But a significant difference between visual and sonic perspective is that the latter is perceived to be in constant flux, and perhaps this is one of its fundamental characterstics.
In Soundscape (1994, p.134), R. Murray Schafer mentions the following environmental effects: reverberation, echo, “drift (fading)” and “displacement (ambiguous point of origin)”. These are all, I think, plausible characteristics of the sound effect in question. In response to my question about the effect, Audio Field Recorder highlights the complexity of the issue:
In the natural world outside there are far too many variables which cannot possibly be taken into account, all of which produce a significant effect on the sound waves as they travel outwards from their source, making it difficult to identify its true location. Some of these are variable air and ground temperatures and localized air pressures from wind effects along the path travelled by the sound waves, localized ground effects which affect wind speed, which in turn affects its air pressure; different frequency filtration by trees, shrubs, grasses crops, reverberation caused by natural ground contours, etc.
To model even one of these variables would be a formidable computational task, so the chance of being able to integrate them all into one effect seems very slim indeed. Nevertheless, it may be that it is not necessary to model all of these variables, because as yet we cannot say to what extent each variable contributes to the effect. To my ears, the most typical element is a sloshing kind of sound, a filtering of the low-mid frequencies that fluctuates up and down. We may be able to visualise some of these fluctuations with a spectrogram of the recording of the F15 dogfight that we listened to earlier (image created with Sonic Visualiser):
The spectrogram image represents the first minute and a half of the recording. Time is represented from left to right, the vertical axis shows frequency on a logarithmic scale, and amplitude is shown in colour – louder sounds are lighter. The bird sounds are easily spotted in the upper portion; the magpie calls can be seen to start around the centre of the image and at the far right a burst of its chatter is visible (click on the image to view it in greater detail). The long duration and slow fluctuation of the wavy bands suggests that they might be due to the sound source (the jet engine) rather than the effect of air at a distance. Notice the clusters of upward-pointing peaks that are more rapidly changing than those wavy bands. I think these visualize the most characteristic sound of the effect – the sloshing, folded, filtered sound. These visible forms do appear to take the form of filters since they appear as dark lines within other sounds. They appear more three-dimensional than the other shapes, perhaps because the peaks seem to occlude each other, like a mountain range. When the spectrogram is viewed in sync with the sound, these patterns appear to correspond to the sounds in question.
I cannot be certain that within these fuzzy images of peaks I have found the effect. Also, we don’t yet know what causes the effect, nor how we might model it. In the next part, I will analyse more sounds and see whether similar patterns are found in other recordings of loud sounds at a distance. It might be possible to use the same process that produces the spectrogram, but in reverse, to generate sound from an image of those clustered peaks.