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Re: [microsound] AI in microsound
I've been using L-Systems to generate images and instructions for
sound. L-Systems are based on strings, so I can breed the initial
strings together, hence genetic programming. I haven't really got very
far, but it's quite a simple approach that can be reapplied in various
audio/visual systems and programming languages without much effort.
The end result I wanted to achieve was based on peer to peer networks.
You know those viruses that spot what you're searching for that create
fake files to try and trick people into downloading them? I wanted to
write a program that waited for users to search for particular
keywords, then generate audio based on my algorithms and their
keywords. Then you'd have little black boxes (as Eno said) hidden in
p2p networks, creating unique tracks.
Maybe someone's done this by now, maybe I'll finish my code one day!
On 21 Mar 2005, at 14:10, david golightly wrote:
For discussion: What AI algorithms are the most useful in microsound
performance - in practice, not only in theory? How many of you
microsounders are using AI algorithms, and what have your experiences
been? Ever used neural networks/second- and third-order Markov
chains/genetic algorithms/generative grammars/other? On what time
scale (piece-structure, moment, sound-event, or microsound
generation)? There was an interesting interview with Brian Eno back in
the 1980's (with The Wire mag, I believe) where he expressed a desire
for a musical "black box" that could produce music in a given style, a
Beethoven black box, a Beatles black box, an Eno black box... Beyond
whatever proprietary concerns are involved, is this even achievable?
There's been a lot of talk of letting your laptop play a wave file vs.
performing the music yourself, but does anyone have any experience
teaching your computer to make desicions for you?
--
homepage: http://alexyoung.org
music: http://noise.me.uk
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