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Yields

by ltfll

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about

"Yields," is my first attempt at generating music with a Markov chain. The music generated by the model is derived from a dataset consisting of six months' worth of consistent improvisation. This dataset includes three MIDI files per day, each lasting five minutes and set to a distinct tempo.

Markov chain is a mathematical model that is used for generating music based on probabilistic transitions between musical states. It represents a sequence of events or states where the probability of transitioning from one state to the other depends only on the current state.

When applied to music generation, a Markov chain can be trained on a dataset of MIDI files, analyzing the patterns and transitions between musical notes or chords. The model then uses this learned information to generate new musical sequences by probabilistically selecting the next note or chord based on the current state.

By leveraging the statistical properties of the training dataset, a Markov chain can create music that exhibits similar patterns and structures to the original data. It offers a method for algorithmic composition and can be a useful tool for generating new musical ideas or imitating a particular style.

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released July 29, 2021

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ltfll Alexandria, Egypt

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