hi william and list,

for a museum-art-installation i will do a kind of audio "social-network"

basically a visitor can record a 5 second snippet via microphone or bluetooth 
and PD saves this snippet as a sample.

out of this ever growing sample-space 8 readsf~ objects  will randomly play 
these samples in various densities to 8 speakers.

so far so easy. (i have implemented that part already)

to get a more social network kind of atmosphere it would be great if newly 
recorded snippets would increase the likelihood of similar material on the 
outputs (as in twitter/facebook/instragram blabla, where you find yourself in 
your bubble)

i still don’t really get howto work with [timbreID] to accomplish this.

maybe someone on the list has an example of this?

the process would be:

-a new sample is recorded (always 5 seconds) -> some [timbreID] analysis 
happens to create a feature-list -> samples with a similar feature-list should 
be played back next (a list of files that are similar would be great)

the number of samples can easily grow to thousand of files, since the 
installation will run for quite some time. each sample is only 441kb though 
(mono 5 seconds file, according to OSX)

the examples of timbreID i look at either look at a fixed soundfile and slice 
it to extract features over time, or slice incoming audio based on onset 
detection for example.
i would just want a feature-list created for each new 5 second clip i record. 

hope this is clear enough, and thanks for reaching out if somebody has done 
something similar..



simon





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