“[I]nformation theory is a mathematical theory of how to optimize a signal for communication in a noisy channel and of how communication degrades in such a medium.” Okay, math is not my cake, but the application of mathematical theory in composing seems interesting and promising. My profession with music was mainly gained from traditional instrument practice (flute). It was by playing in the school’s orchestra team that I learned more theories (in English), but I’m still quite limited in music accomplishment and composing. In the meantime, I do know that music and composing have been involving more and more math and programming as new media emerge. It is again, in fact, stimulating our thoughts on computational creativity.
Laurie Spiegel thinks that random noise can be meaningful signals in other contexts. That makes sense considering the noise of repairing roads. However, I’m not sure how to position the purely numerical randomness in digital music. For d1 $ sound “hh*8” # gain (range 0.8 1.5 rand), what is the context that makes more sense and what is not? Furthermore, Spiegel claims that at the essence of auditory imagination is just re-generation/transformation of previous materials in humans’ perceptual and cognitive systems. In that case, computational creativity might not be about creating something completely new, but new “permutation and combination” that can trigger emotional reactions in certain environments.
What I didn’t see discussed is the subjectivity about creation (composing). Yes, noise works. Entropy variable works. The outcome does affect audiences’ emotions, but what about the composer? Creating compositional models should definitely be different from traditional composing regarding subjective experience and reward. Making an analogy with “art” versus “design”, this process seems more like design: it’s using principles to create things for people.
Written in 1997, the article already looks quite advanced for me. I wonder what has changed, and what new theories or models have appeared from that time till now.