After developing a microphone wind noise detector which is trained on simulated examples of wind noise (see my ICME conference paper), rigorous proof of the algorithm’s success (or failure!) is required. In fact the reviewers of this aforementioned paper suggested this. To that aim I packed a car full with microphone stands, cables, preamps, and a number of recording devices and set off to collect some examples of wind noise.
The requirement for the location to collected these examples is that there is very low levels of background noise. I found a location up upon Rivington Pike, north of Manchester. There was a road which was closed for repair, ideal! as it means no traffic. After a couple of false starts and some help from a kindly local man, I found a good location with, no road, rail, urban or air traffic noise. I located a place away from trees, which can create a surprisingly loud level of rustling noise and set my microphones up.
I was using an Edirol R-44 to capture four channel of audio onto an SD card at 44.1 kHz sampling frequency. I set up two measurement microphones, one with a wind shield, a sure SM58 dynamic microphone, a zoom H2 recorder and an iPhone taped to a stand. Though one of my microphones sported a windshield, due to the particularly blustery conditions with 20 mph winds, wind noise was present on all recordings. This made it all the more important that the background sound level was as low as possible as I intend to compute the wind noise level, assuming that the background noise level is negligible.
- recording device used, 4 channels
- Calibration was carried out on the two measurement microphones by placing a calibrator on each, playing a 1 kHz tone at around 94dB and recording these sounds. Now I can calibrate my recordings so that I can present data in the actual sound pressure levels recorded for these two microphones. To calibrate the other devices is a little tricky, but a 1 kHz tone was played back over a loudspeaker at approx 1m distance and recorded on all devices simultaneously. As I can now know the true sound pressure level from the calibrated measurement microphones, i can also compute the true level of this tone relative to the calibrated recordings and using this information calibrate the other microphones to within a few decibels. To remove wind noise a narrow band-pass filter is applied centered on 1 kHz. Clearly there is some error due to the location of the microphones and and residual wind noise present within the pass-band, but this is not a significant problem.
- Several hours later, and I am rather cold but have the data, now back to Salford set up my validation procedure.