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Old 2013-02-17, 11:11
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audax audax is offline
Join Date: Sep 2007
Posts: 44
Originally Posted by budbjames View Post
I don't think that this idea is crazy at all. I believe that the possibilities of machine learning are limited only by the data that we have available to provide. I could see how ML could be used in reason to learn parameters that are common to certain styles of music. you could then set a preset and perhaps set a randomization seed.. and you would get a unique, but relevant set of parameters for your specified style preset. Machine learning is the future.. Great question!

Buddy James
thanks for your answer
it would be interesting to know a minimal set of possible parameters sufficient enough to represent the learned data (eg. sound). as a starter, there are some time-dependent ml algorithms out there or, that can model timed continuous data rather well, hence
we could go even further and extend the concept of learned parameters to a new kind of sound synthesis. as these two papers rely on a relatively simple energy based ml algorithm, it would be possible to generate sounds from previously learned samples (sometimes called daydreaming in context of visual computing) and it could also be possible "to do" some other forms of remixing

generally speaking ml is the future (or has ever been) but a ml algorithm based synth wouldn't be so easily accessible to everyone (learning couldn't be done online or live, generated samples would be non deterministic etc...). however, i would be happy to see an experimental impl. inside reason

ps: it would be nice to have the sdk. unfortunately there are some restrictions :/

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