MCMChaos: Improvising Rap Music with MCMC Methods and Chaos Theory
This is an incremental novelty for music generation enthusiasts, applying existing mathematical methods to a new domain without broad impact.
The authors tackled rap music generation by developing MCMChaos software that uses MCMC methods and chaos theory to alter speech parameters like rate and volume in real-time via a GUI, resulting in a novel application of these mathematical simulations to rap.
A novel freestyle rap software, MCMChaos 0.0.1, based on rap music transcriptions created in previous research is presented. The software has three different versions, each making use of different mathematical simulation methods: collapsed gibbs sampler and lorenz attractor simulation. As far as we know, these simulation methods have never been used in rap music generation before. The software implements Python Text-to-Speech processing (pyttxs) to convert text wrangled from the MCFlow corpus into English speech. In each version, values simulated from each respective mathematical model alter the rate of speech, volume, and (in the multiple voice case) the voice of the text-to-speech engine on a line-by-line basis. The user of the software is presented with a real-time graphical user interface (GUI) which instantaneously changes the initial values read into the mathematical simulation methods. Future research might attempt to allow for more user control and autonomy.