The document discusses machine learning approaches for harmonizing melodies. It describes how machine learning models like hidden Markov models and neural networks can be trained on datasets of melodies and their corresponding chords to learn patterns and generate harmonized accompaniments for new melodies. The training data includes elements like the melody, past chords, and tempo. The trained models can then be used to predict chords for an input melody and output a harmonized version.
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