On Sun, 11 Oct 2009, Jerome Covington wrote:
Is anyone interested in sharing their process for turning real-time, non-audio data feeds, into music? See a great example of one possible direction, here.
Coïncidentally, I wrote some thoughts about it in the Pd chatroom a few hours before your email, because of a similar topic there:
«musical meaningfulness comes from meaningfulness of the data beforehand... basically, if you put garbage in, you get garbage out.
the exception to that is that a programme is a kind of data in itself, so the programme can be considered a kind of meaningful input... and if the programme imposes itself as the source of the meaning and successfully downplays the incoming garbage, it can make the output meaningful;
but unless one is very skilled at understanding the information theory standpoint of music, using random values gives you just more meaningless music like what you are talking about... sort of like picking a random book from the library of babel.
»
http://vimeo.com/5415629
now this is what I add to my above thoughts, this time in relationship to the video: without necessarily explicitly thinking about information theory, one can get to interesting results intuitively... one essentially has to focus on getting beautiful results for likely inputs instead of being content with whatever fits with the description of a certain art concept. Any former stock-market music I had listened to sounded like crap. What Patrick did was to make his programme insert so much beauty and coherence in the market's noise, that it made it sound meaningful... actually, it's more like this: the programme can only output music that sounds reasonably good no matter the input, and the meaningless input selects one of the possible nice-sounding outputs. Overall, the music is more shaped by Patrick's æsthetic decisions than by the stock market, and it's perfect like that.
so, Jérôme, I would mostly just suggest that you make patches so that the results sound fairly good no matter the input you give them, and optionally, if you can make the input also recognisable in the output, it's a bonus feature that can feel very rewarding, but it depends on the context... for feeding stockmarket data it may not matter as much, but for live interactive data from performers or visitors, they have to recognise their own impact on the music, else the point is going to be lost on them, really. but even for stockmarket data, it's better if you can recognise the stock price in the music, because if you can't, you could have taken that data from anywhere else and it wouldn't matter, so why would you call it stockmarket music then?...
so maybe you wanted people to explain their actual processes, but I hope that you will also enjoy this reflexion on the question of what might make processes be good or not.
_ _ __ ___ _____ ________ _____________ _____________________ ... | Mathieu Bouchard, Montréal, Québec. téléphone: +1.514.383.3801
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