You might be missing the point somewhat. With these methods, you could eg. test the vast swaths of potentially overlooked composers to see if any of them merit closer listening.
Very highly unlikely. The method in the paper isn’t measuring quality or novelty or authenticity or listenability or anything useful for evaluating composers without listening to them. It’s measuring the compressibility of MIDI files. We already know that Bach is less compressible than Philip Glass, and more compressible that Charles Ives. The methods in this paper cannot tell you if a composer is boring or derivative, nor whether they’re fresh and innovative for their time. They also can’t tell you anything about a performance. I mean go ahead and try, I’m all for experimenting, but I predict that trying to apply this paper to looking for overlooked composers will be an exercise in sifting through noise, more effort than searching manually, and spending time writing code instead of listening to good music.
I think (have never tried) that analyzing the harmony and rhythm (can you quantify syncopation?) you’d have a good start at determining if a song is worth listening to.
First, the methods of the paper don’t have to be a Mendelssohn replacement to be useful. Second, if you don’t like that potential application, consider all the other predictive models that could benefit from these features.
dahart|2 years ago
memset|2 years ago
macrolocal|2 years ago
First, the methods of the paper don’t have to be a Mendelssohn replacement to be useful. Second, if you don’t like that potential application, consider all the other predictive models that could benefit from these features.