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(HACKACM 2019) Given an input of single-melody MIDI files, parse them and record data into Markov chains, which then are used to algorithmically generate new MIDI files characteristic of their input. EXAMPLE OUTPUT: https://youtu.be/O5wizLRBNq0

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HACKACM 2019

Alex Lill and Tyler Batistic

Predictive Music (Example output at https://youtu.be/O5wizLRBNq0)

Deconstructs and parses .mid files and inputs data into Markov chains, which are then used to algorithmically generate new MIDI files which are characteristic of their input.

We use a selection of Charlie Parker MIDI files, whose data is collected, processed, and used to generate jazz-influenced compositions.

INSTRUCTIONS:

Compile ReadMidi.java, MusicMarkov.java, and MusicWriter.java. Main is inside MusicWriter. After running, a new file, out.mid, will be generated and saved within the same directory as the code files. It can then be opened by any midi interpreter.

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(HACKACM 2019) Given an input of single-melody MIDI files, parse them and record data into Markov chains, which then are used to algorithmically generate new MIDI files characteristic of their input. EXAMPLE OUTPUT: https://youtu.be/O5wizLRBNq0

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