This blog documents the process of teaching an AI system to generate melodies from the Skiptune database. Expect experiments, mistakes, and occasional surprises, and at the end expect melodies that sound as if a human wrote them.
This week we perform our last analysis of Heaps Law using 2-note words, and we do so by shuffling the database 1,000 times and performing a Heaps Law analysis on each one, calculating the statistical properties of that shuffled deck, and compare it to our year-ordered analysis. The results are highly informative. We start with…
The next part of our exploration into Heaps Curves is to analyze the Skiptune corpus after it has been ordered by year of composition and publication. As this is a blog, we are constantly updating and adding to the database between the weekly publications. At this point, we happen to have an even 83,400 number…
We now turn our attention to Heaps’ Law when our musical word is defined not as a single note, but as a note followed by the next note in a melody. This 2-note pairing will increase the vocabulary size, so we would expect results placing the Skiptune database a little closer to Heaps’ Curves as…
This week we check to see how much of our two choices of ordering the database, as entered and by year, are typical of random orderings. We test that by shuffling the order of the database 1,000 times, and then running the Heaps Law analysis one thousand times, one for each row or tune in…