As a birder, this looks like a failed experiment to me. Or I don't understand what their goal was. The groupings make little sense in terms of what these species sound like. I'm guessing that's an artifact of the way they sampled the sounds, losing macro properties. Kind of like grouping the words 'paramour', 'enmity' and 'hamster' together bc they all contain /m/ sound.
Unfortunately they only hint at the envisioned application in the video and don't provide any further links, but the idea is amazing: Use sounds to monitor bio-diversity. Imagine we'd not need cameras and lots of luck to "catch" proof of an animals existence but a grid of interconnected omnidirectional microphones. We'd get real time tracking of individual animals in 3D and could have smartphones literally point the way to yet uncatalogued or even undiscovered species.
From the video, it appears this is an AI-plotted hugely multidimensional space t-sne'd onto two dimensions.<p>Would be interesting to do some kind of ML on how best to present hugely multidimensional spaces onto two _interactive_ dimensions. Where one AI is deciding how things are projected and how it can be manipulated, and another AI is limited to some virtual "mouse, keyboard, 2D screen" to make inferences. Such that it's optimized for faster, more correct inferences.
more like sorting bird sounds, not visualizing...<p>The tiny images are just spectograms/fft as far as I can tell.<p>edit: it's very fun though to click+drag, haha
There are some instances of the same bird in multiple locations (great horned owl). Presumably multiple recordings of the same bird. My initial reaction to them not being neighboring is to wonder about the quality of the result. Maybe better feature engineering needed to make this biologically relevant. Any other interpretations?
It would be interesting to see how similarity in bird call behavior tracks (or doesn't) the phylogenetic relationship between species. My hypothesis would be that bird calls are influenced by other birds in the same ecosystem (imitation or differentiation, and reflecting a high degree of cultural learning) rather than the null hypothesis of genetic transmission.
Interesting, spammed a few bird lovers i know with it. Though they almost all replied the recordings are not good enough.<p>Though personally (jk) i was slightly disappointed when i zoomed out i didn't see a big bird (or other bird) likeness.
I poked around and also looked at a similar experiment, the Infinite Drum Machine: <a href="https://aiexperiments.withgoogle.com/drum-machine" rel="nofollow">https://aiexperiments.withgoogle.com/drum-machine</a><p>Does anyone know what they are doing t-SNE on? i.e. are they just doing t-SNE on the raw waveforms? Or the MFCC spectrogram? Or what?
It's interesting, at the very local level I think most humans wouldn't think two adjacent bird sounds are all that similar. But if you drag along a long line and listen to a series of different birds you can "hear" a definite organized progression that seems to be organizing rhythm and major tones into groups.
It's good to see Google in the last couple of weeks launching a bunch of [1]projects that are more in line with their mission of 'organising the world's information'.<p>[1] <a href="http://www.smithsonianmag.com/smart-news/google-digitizes-3000-years-fashion-history-180963633/?no-ist" rel="nofollow">http://www.smithsonianmag.com/smart-news/google-digitizes-30...</a>