Abstract / Synopsis
Random generation of music goes back at least to the 1700s with the introduction of Musical Dice Games. More recently, Markov chain models have been used as a way of extracting information from a piece of music and generating new music. We explain this approach and give Python code for using it to first draw out a model of the music and then create new music with that model.
DOI
10.5642/jhummath.202102.08
Rights Information
Mark Huber and Illana Shapiro
Recommended Citation
Ilana Shapiro & Mark Huber, "Markov Chains for Computer Music Generation," Journal of Humanistic Mathematics, Volume 11 Issue 2 (July 2021), pages 167-195. DOI: 10.5642/jhummath.202102.08. Available at: https://scholarship.claremont.edu/jhm/vol11/iss2/8
