Abstract
The goal of this research is to maximize chord-based composition possibilities given
a relatively small amount of information. A transformational approach, based in group theory,
was chosen, focusing on chord intervals as the components of a modified Markov process. The Markov
process was modified to balance between average harmony, representing familiarity, and entropy,
representing novelty. Uniform triadic transformations are suggested as a further extension of the
transformational approach, improving the quality of tonality. The composition algorithms are
demonstrated given a short chord progression and also given a larger database of albums by the
Beatles. Results demonstrate capabilities and limitations of the algorithms.
a relatively small amount of information. A transformational approach, based in group theory,
was chosen, focusing on chord intervals as the components of a modified Markov process. The Markov
process was modified to balance between average harmony, representing familiarity, and entropy,
representing novelty. Uniform triadic transformations are suggested as a further extension of the
transformational approach, improving the quality of tonality. The composition algorithms are
demonstrated given a short chord progression and also given a larger database of albums by the
Beatles. Results demonstrate capabilities and limitations of the algorithms.
| Original language | American English |
|---|---|
| Pages (from-to) | 43 |
| Number of pages | 1 |
| Journal | Math. Comput. Appl. |
| Volume | 25 |
| Issue number | 3 |
| DOIs | |
| State | Published - 1 Jul 2020 |