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.
When Skiptune was started at the turn of the last century, machine learning was rudimentary and artificial intelligence (AI) was limited to such accomplishments as turning speech into text. Accuracy was 85 to 95 percent, which means 10 mistakes every 100 words. Face detection was limited to detecting a face, but not identifying it.
Problem to Be Solved The Skiptune database is a database of 83,000 melodies from around the world and across several centuries. These melodies are encoded in a special way (a pitch difference followed by a duration ratio), and we want to explore whether an AI model can learn melodic structure from this representation. The