After Douglas Eck’s presentation of Magenta, Google’s TensorFlow offshoot and (market-oriented) research into generative kitsch, I’d like to pose a question on what I’d call the issue of euphony. I’m broadly and loosely calling euphony what makes Music sound good not only as it pertains to a particular canon or tradition, but also what makes Music sound good independently of canons and traditions. Here’s my question:
Is there any Machine Learning research being done to probe cross-canonical and cross-traditional corpora in order to discover Weltmusik (or Géomusique, as Deleuze would put it), i.e. the (hypothetical) generative topos/space of good-sounding Music independently of canons and traditions?
If, as I suspect, there is indeed (some approximation of) such a generative topos/space waiting to be discovered beneath the buoyant surface of Global Music History, I’d really love to explore it theoretically and creatively — to know and understand it of course, and ideally even to experiment with potentially new and unheard forms of good-sounding Music — with all the computational (Machine Learning) tools available to us.
Any hints or insights, as well as any fleeting/free-floating thoughts, on this issue would be much appreciated.
All the best,