A Transformational Approach to Harmony Improvisation
Meirav Amram, Etan Fisher, Shai Gul, and Uzi Vishne

This paper introduces a transformational approach to harmony improvisation within the framework of a Markov decision system. Group theory provides the mathematical background of the transformational approach. While chord progressions are the acceptable basis for harmony composition using Markov models, the transformational approach is interval-based. The capabilities and limitations of the transformational approach are demonstrated and discussed, then enhanced using a UTT-based approach. A decision system optimizes the balance between compatibility, represented by average harmony, and variety, represented by entropy. Musical examples are presented, including sequence matching that demonstrates consistency and sensitivity to the decision parameters.
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