3 ms·
Sampling at 48kHz seems like overkill. If you record at a lower sample rate (e.g. 22k) you will still be able to detect the bubbles, but the files will be about
by supernes 9y ago
Sampling at 48kHz seems like overkill. If you record at a lower sample rate (e.g. 22k) you will still be able to detect the bubbles, but the files will be about 4 times smaller, and as an added bonus it will function as a sort of high cut filter, which may help with stray high frequency noises or thermal noise (to some extent). Additionally, you can apply a band pass filter around the frequency of the popping, if you aren't already cleaning it up before processing. Given a clean recording, you can trim the silence and still have full sample data for re-running algorithms on later if you preserve the timing metadata.
You could match the spectral signature to a known sample to distinguish between bubbles popping and other types of noises, if there were any, but the recording conditions seem good enough not to warrant it.
You could also possibly use an array of two, three or more mics and do some fancy triangulation to get a 3D map of the pop locations and better distinguish between individual pops, but I doubt how useful that would be besides a few cool visualizations.
- anfractuosity 9y agoYeah I agree with respect to the sample rate. I wasn't really sure what sample rate would be best when I started recording the audio, so just picked the highest the soundcard could handle. I'll definitely look into applying a bandpass filter, thats a good idea! I had wondered about the spectral signature idea, I was wondering if I could simply slide a window across the data, applying some kind of correlation function, using the magnitude data from the FFT of a known 'bubble' output compared to the window. But I wasn't sure what kind of correlation function to use, whether maybe Pearson correlation coefficient would be sensible? I like your idea of using multiple microphones to get a 3D visualisation.
- cocoablazing 9y agoYou are better off squaring the signal. Applying an FFT to get the magnitude will smear your signal in time. I suggest you look into acoustic emission detection.
- anfractuosity 9y agoThanks! I'd not heard of acoustic emission detection, I'll look into that now. Do you think my sample rate is high enough for acoustic emission detection, as I notice in your other comment you mention they often use sample rates many times higher. Also is there a particular paper you'd recommend regarding acoustic emission detection?
- cocoablazing 9y agoSince bubbles popping are a random and impulsive source, the spectrum of the detected noise will be the resonance of the glass plus a white noise floor. 48khz is not overkill. Acoustic emission sensors used to detect signals like this typically use many times that sampling rate.