Music thread

Bandcamp is great, though I guess other sources are okay too. Post music you like.
https://slipimprint.bandcamp.com/track/night-howl
https://nekophiliac.bandcamp.com/track/current-thoughts-and-feelings
https://mintsyrup.bandcamp.com/track/sleeptimer
https://soundcloud.com/syrup/6292-feativy
https://soundcloud.com/syrup/recursive-functions
https://goreshit.bandcamp.com/track/2nd-dose-here
https://blueyeong.bandcamp.com/track/your-skin-can-turn
https://ethereeeal.bandcamp.com/track/cosmic-latte
https://beakrot.bandcamp.com/track/kusa-kusa
http://music.businesscasual.biz/track/8am
https://chicodub.bandcamp.com/track/catacumba-urubu
https://theworstlabel.bandcamp.com/track/ingen-s-g-det
https://elemental95.bandcamp.com/track/botanical-gardens
https://tesslesstess.bandcamp.com/track/life-on-raroia
https://goreshit.bandcamp.com/track/three-times
https://marsargo.bandcamp.com/track/runaway-runaway
https://lomelda.bandcamp.com/track/interstate-vision

>>1
I exclusively listen to pure sine waves from binaural beat presets that loop each 24/7. I had a videogame midis collection from the site vgmusic, but i haven't listened to them since late 2000's.
Music is in essential form a chaotic form of mixed sine waves, so you're listening to random garbage+vocals. I select the sine waves most useful for the time of day, for their frequency's brainwave shaping effect - for night sleep, waking, morning, midday,evening, late night.

>>121
fuck off with your pseudointellectual reductionist garbage

music isn't about sine waves and shit

it's about rhythms and emotions

atmospheres and moods

moments and reflections

memories of things that once were

thoughts of things that will be

enjoying yourself in the now

https://mekusongies.bandcamp.com/album/miscalculations

>>123
These are associative reinterpretations. Sounds have no inherent meaning, only frequency and amplitude.

>>122
Speaking of reductionism, you can use it to find frequency for sine wave generation.
You can isolate the exact sounds you like in a song. Just cut the song in half, check which part you like. Cut it again in half or discard a random chunk. Keep cutting until you have a segment you particularly like.
Put it on repeat. You now have a toneset, you can analyse it in audacity with frequency analysis(Analyze->Plot Spectrum->see highest peak in frequency).