Does anyone know of anyone researching into the identification of different noises, as opposed to distinct sounds, and can they point me at them please?
By "Noise" i mean multiple asynchronous multi-source sounds which equate to radio "Squelch", and by "Sounds" I mean single source audio output which can be identified (with practice).
We are working on identifying large flocks of birds who all tweet and flap asynchronously at www.withymbe.info
25 September 2020 8:36pm
This is also an issue in marine acoustics that I have worked on. To improve detection of the target sounds you need to develop classifiers for the soundscape i.e. your noise, and then build an adaptive response to that noise. In the marine ultrasound context the noise may be sediment transport noise (huge and varied - many weak sounds), wave noise, shrimp noise (fewer very loud transients), boat sonars, acoustic modems, unknown biolgogical sources (diel chorusing is common and sources generally unknown) etc etc so this requires a layered approach to classifier development. ... but then you hit the problem of getting good generalization performance when you have too few soundscapes and many cannot be labelled. So it is a limiting factor.
I'm guessing that the terrestrial problem is easier because sources are much more often known, but that's not a lot of help to you!