Hear 1,500+ Genres of Music, All Mapped Out on an Insanely Thorough Interactive Graph

If you are ready for a time-suck inter­net expe­ri­ence that will also make you feel slight­ly old and out of step with the cul­ture, feel free to dive into Every Noise at Once. A scat­ter-plot of over 1,530 musi­cal gen­res sourced from Spotify’s lists and based on 35 mil­lion songs,  Every Noise at Once is a bold attempt at musi­cal tax­on­o­my. The Every Noise at Once web­site was cre­at­ed by Glenn McDon­ald, and is an off­shoot of his work at Echo Nest (acquired by Spo­ti­fy in 2014).

McDon­ald explains his graph thus:

This is an ongo­ing attempt at an algo­rith­mi­cal­ly-gen­er­at­ed, read­abil­i­ty-adjust­ed scat­ter-plot of the musi­cal genre-space, based on data tracked and ana­lyzed for 1,536 gen­res by Spo­ti­fy. The cal­i­bra­tion is fuzzy, but in gen­er­al down is more organ­ic, up is more mechan­i­cal and elec­tric; left is denser and more atmos­pher­ic, right is spiki­er and bounci­er.

It’s also egal­i­tar­i­an, with world dom­i­nat­ing “rock-and-roll” giv­en the same space and size as its neigh­bors choro (instru­men­tal Brazil­ian pop­u­lar music), cow­boy-west­ern (Con­way Twit­ty, Mer­le Hag­gard, et. al.), and Indi­an folk (Asha Bhosle, for exam­ple). It also makes for some strange bed­fel­lows: what fac­tor does musique con­crete share with “Chris­t­ian relax­i­tive” oth­er than “rea­sons my col­lege room­mate and I nev­er got along.” Now you can find out!

Click on any of the gen­res and you’ll hear a sam­ple of that music. Dou­ble click and you’ll be tak­en to a sim­i­lar scat­ter-plot graph of its most pop­u­lar artists, this time with font size denot­ing pop­u­lar­i­ty and a sim­i­lar sam­ple of their music.

I’ve been spend­ing most of my time explor­ing up in the top right cor­ner where all sorts of elec­tron­ic dance sub­gen­res hang out. I’m not too sure what dif­fer­en­ti­ates “deep tech house” from “deep deep house” or “deep min­i­mal tech­no” or “tech house” or even “deep melod­ic euro house” but I now know where to come for a refresh­er course.

Spo­ti­fy and oth­er ser­vices depend on algo­rithms and tax­onomies like this to deliv­er con­sis­tent lis­ten­ing expe­ri­ences to its users, and they were attract­ed to Echo Nest for its work with gen­res. Echo Nest was orig­i­nal­ly based on the dis­ser­ta­tion work of Tris­tan Jehan and Bri­an Whit­man at the MIT Media Lab, who over a decade ago were try­ing to under­stand the “fin­ger­prints” of record­ed music. Now when you lis­ten to Spotify’s per­son­al­ized playlists, Echo Nest’s research is the engine work­ing in the back­ground.

McDon­ald says in this 2014 Dai­ly Dot arti­cle this isn’t about a machine guess­ing our taste.

“No, the machines don’t know us bet­ter than we do. But they can very eas­i­ly know more than we do. My job is not to tell you what to lis­ten to, or to pass judg­ment on things or ‘make taste.’ It’s to help you explore and dis­cov­er. Your taste is your busi­ness. Under­stand­ing your taste and sit­u­at­ing it in some intel­li­gi­ble con­text is my busi­ness.”

If you’d like a more pas­sive jour­ney through the ever expand­ing music genre uni­verse, there’s a Spo­ti­fy playlist of one song from each genre (all 1,500+) above. See you in the deep, deep house!

via Kottke.org

Relat­ed Con­tent:

The His­to­ry of Hip Hop Music Visu­al­ized on a Turntable Cir­cuit Dia­gram: Fea­tures 700 Artists, from DJ Kool Herc to Kanye West

Crime Jazz: How Miles Davis, Count Basie & Duke Elling­ton Cre­at­ed Sound­tracks for Noir Films & TV

Pio­neer­ing Elec­tron­ic Com­pos­er Karl­heinz Stock­hausen Presents “Four Cri­te­ria of Elec­tron­ic Music” & Oth­er Lec­tures in Eng­lish (1972)

Ted Mills is a free­lance writer on the arts who cur­rent­ly hosts the FunkZone Pod­cast. You can also fol­low him on Twit­ter at @tedmills, read his oth­er arts writ­ing at tedmills.com and/or watch his films here.