The definitive work on stochastic approaches to mimicking musical style
is that of David Cope:
http://arts.ucsc.edu/faculty/cope/
He does all his work in Common Lisp (ugh!) but it's really good stuff,
and the results are very impressive.
-Paul
Achim Schneider wrote:
Henning Thielemann <[EMAIL PROTECTED]> wrote:
On Thu, 5 Jun 2008, Achim Schneider wrote:
The recent discussion about Markoff chains inspired me to try to
train one with all the Bach midi's I have on my disk, collecting
statistics on what intervals tend to get played simultaneously,
which follow others and in which way the pitch offsets from its
mean, so that melodies fall and raise "naturally".
I don't know, if you already found that one:
http://darcs.haskell.org/haskore/src/Haskore/Example/Kantate147.hs
Surprisingly I also tried Markov Chain on a Bach song. But my
approach was too simplistic in order to produce a nice new song.
Yes, you need to take both dimension of music into account, that is
time and polyphony. Bach uses quite exceptional polyphony from time to
time, but it always stays harmonious: You have to have eg. a 0%
probability of ever playing a note and its minor second. The
probability of a note and its quint will most likely be at least 50%,
but then there are chords that sound atrocious if it's there.
What I need is basically one view of the data as list of used chords,
and one graph of all possible time-linear progressions... that is,
voices, for a definition of "voice" that makes the guitarist in me
shudder.
Seems like I'm going to make close acquaintance with fgl, after all.
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