Simple markov music generator

1. Read a MIDI file and convert that to an internal representation.

2. Model as a Markov process: Populate matrix of transition probabilities.

3. Use the learned model to generate a music sequence based on some initial state.

Typical paradigm of operations

1. Prune the MIDI file to contain a single channel with no polyphony. Use various commands (as seen in Akarsh's scratch file) to identify various aspects of the MIDI file. Set these parameters in all the python scripts.

2. Run midi-to-unigrams.py to generate a list of unigrams from the MIDI file. This program dumps to stdout, so you might want to redirect the output into a file. The input MIDI file is set in the python script.

3. Run unigrams-to-ngrams.py to generate a list of n-grams from the MIDI file. The input file is specified in the python script. The program dumps to stdout, so you might want to redirect the output into a file. The 'n' of n-grams is specified inside the file. Last few notes may be clipped, especially for large 'n'.

4. Run the appropriate scripts to generate the Markov model (TODO: Fill in details).

5. Run the appropriate scripts to generate random realizations of the Markov model (TODO: Fill in the details).

6. Convert the n-grams from the Markov model back into unigrams using ngrams-to-unigrams.py. This script takes the input file on the command line (as the first argument), and outputs to stdout.

7. Resynthesize a MIDI file from the unigrams. The script takes both the input file (first argument) containing unigrams and the output MIDI file (second argument) as command-line arguments. Tempo, instrument, transpose and other settings are specified in the python script.

Conceptual reading

For a simple introduction to the concept of Markov chains, check http://austingwalters.com/introduction-to-markov-processes/