The knowledge base for such a validation system can probably be lifted from any good music theory book or website. The downside in this case is that they require continuous human feedback to assess the fitness of the newly evolved patterns.Īn expert system can be used to verify sequences generated by the other techniques. A simple model could use a binary chromosome in which the first 32 bits represent the pattern of a kick drum, the second 32 bits a snare, the third 32 bits a closed hi hat and so on. Genetic algorithms can be used to evolve rhythm sections. You can choose to incorporate this information into the Markov chain states or neural network outputs, or you can generate it separately and combine the independent pitch and duration sequences. In addition to pitch you will need duration to determine the rhythm of the generated notes or chords.
I can't think of any benefit over the Markov chain approach other than reducing the memory footprint. The end result will be similar to that of the Markov chain approach.
#Random music generator algorithm series
Neural networks are well suited to time series prediction (forecasting), which means they're equally suited to 'predicting' a musical sequence when trained against existing popular melodies/harmonies. For harmony generation, try a combination of key-relative note numbers for the root of the chord, the type of the chord (major, minor, diminished, augmented, etc.) and the inversion of the chord (root, first or second).if the key is C minor, C would be 0, D would be 1, D# would be 2 and so on) For melody generation, try key-relative note numbers (e.g.The real beauty of Markov chains is that the states can be whatever you want. This method requires analysis of existing songs to build the chain transition probabilities. Markov chains, for instance, are well suited for melodic and harmonic sequence generation. I doubt you'll find one technique that works well for melody, harmony, rhythm and bass sequence generation across all genres of music. The most successful system will likely combine several techniques.
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