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I started down this road, and have amassed a small collection of files made up of just the first ten and last ten seconds of demixed tracks of every song in my

I started down this road, and have amassed a small collection of files made up of just the first ten and last ten seconds of demixed tracks of every song in my library I hoped to put together a system that compares the backs to the fronts and lists the output to find cool transitions, but I have no idea how to actually "grade" the similarities Beyond basic BPM matching on the drums tracks, nothing I've tried has made for anything really compelling (sounds random... :( )

sevagh 3y ago
OK, so, tangentially related: I tried to do something once - I took small chunks of songs generated by SampleRNN in an attempt to stitch together the ones that sounded the most similar to create a much longer track. The script [1] uses Essentia Chromaprint [2] to "grade" the similarity of audio tracks, and combine the ones with the closest chromaprint. No crossfade or BPM matching, just yolo concatenation. I have a track on Soundcloud which uses the above technique (mashing together short generated clips by their chromagram), trained on Cannibal Corpse [3] 1: https://github.com/sevagh/1000sharks.xyz/blob/master/samplernn-scripts/curation.py https://github.com/sevagh/1000sharks.xyz/blob/master/sampler... 2: https://essentia.upf.edu/reference/std_Chromaprinter.html https://essentia.upf.edu/reference/std_Chromaprinter.html 3: https://soundcloud.com/user-167126026/1000sharks-domainal-skeleton?in=user-167126026/sets/1000sharks-ai-generated-metal&si=ab01893e5c864f33bb5cea170877ce09&utm_source=clipboard&utm_medium=text&utm_campaign=social_sharing https://soundcloud.com/user-167126026/1000sharks-domainal-sk...
tristanc 3y ago
Interesting, I attempted to do the same as you but stopped just shy of BPM matching. However I did get sound similarity working using an audio tagging neural net [1]. I chopped off the first and last 15 seconds of every song in my collection and ran them all through this analysis which produces a ~520 dimensional vector. I then targeted specific endings I wanted to match and used Euclidian distance to find the closest matching song beginning. YMMV but I thought it actually worked pretty well, I just never got to automating the BPM matching. I can try to look for my old script if you're interested :) [1] https://github.com/fschmid56/EfficientAT https://github.com/fschmid56/EfficientAT
kbouck 3y ago
my idea was to let an existing app like djay do the beat matching (which it does really well!) and demixing (less well), and then make a custom app that would act like a midi controller, adjusting the vocals, beats, melody while songs are transitioning, perhaps working off of cues bookmarked in the songs.

sevagh 3y ago

OK, so, tangentially related: I tried to do something once - I took small chunks of songs generated by SampleRNN in an attempt to stitch together the ones that sounded the most similar to create a much longer track. The script [1] uses Essentia Chromaprint [2] to "grade" the similarity of audio tracks, and combine the ones with the closest chromaprint. No crossfade or BPM matching, just yolo concatenation. I have a track on Soundcloud which uses the above technique (mashing together short generated clips by their chromagram), trained on Cannibal Corpse [3] 1: https://github.com/sevagh/1000sharks.xyz/blob/master/samplernn-scripts/curation.py https://github.com/sevagh/1000sharks.xyz/blob/master/sampler... 2: https://essentia.upf.edu/reference/std_Chromaprinter.html https://essentia.upf.edu/reference/std_Chromaprinter.html 3: https://soundcloud.com/user-167126026/1000sharks-domainal-skeleton?in=user-167126026/sets/1000sharks-ai-generated-metal&si=ab01893e5c864f33bb5cea170877ce09&utm_source=clipboard&utm_medium=text&utm_campaign=social_sharing https://soundcloud.com/user-167126026/1000sharks-domainal-sk...

tristanc 3y ago

Interesting, I attempted to do the same as you but stopped just shy of BPM matching. However I did get sound similarity working using an audio tagging neural net [1]. I chopped off the first and last 15 seconds of every song in my collection and ran them all through this analysis which produces a ~520 dimensional vector. I then targeted specific endings I wanted to match and used Euclidian distance to find the closest matching song beginning. YMMV but I thought it actually worked pretty well, I just never got to automating the BPM matching. I can try to look for my old script if you're interested :) [1] https://github.com/fschmid56/EfficientAT https://github.com/fschmid56/EfficientAT

kbouck 3y ago

my idea was to let an existing app like djay do the beat matching (which it does really well!) and demixing (less well), and then make a custom app that would act like a midi controller, adjusting the vocals, beats, melody while songs are transitioning, perhaps working off of cues bookmarked in the songs.