folk-rnn composition competition

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Humours Of Time Pigeon, The

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Eight short outputs generated by a long short-term memory network with three fully connected hidden layers of 512 units each trained on over 23,000 ABC transcriptions of session music (Irish, English, etc.), and arranged by my own “personal” neural network trained on who knows what for who knows how long (I can’t remember any of the settings) (2015)

  1. Hole's Mill (1:30)
  2. Segue: The Birthday (0:09)
  3. A Fhsoilah Kilnie (1:14)
  4. The Humours Of Time Pigeon (0:33)
  5. The Arian (3:02)
  6. Segue: Larkin's With A Coma Pile Phana (0:28)
  7. Bump Of Howled Sho The fetch (2:38)
  8. Segue: Barch Beach (0:10)

These eight short pieces come from my recent explorations of using deep learning to assist the process of music composition. The training of the text-based network aims to make it produce the “correct” output character following a given input character from training data. The end result is a generative system from which we can sample any amount of output. The network also produces titles in its output. While the system output often exemplifies the conventions in its training data (e.g., Irish and English folk music, see The Endless Traditional Music Session), it sometimes produces surprises. These pieces come from such surprises. (More info: https://highnoongmt.wordpress.com/2015/08/15/deep-learning-for-assisting-the-process-of-music-composition-part-4/)

Acknowledgments: Andrej Karpathy for his open source char-rnn code; João Felipe Santos for help in training and sampling the network; thesession.org contributors.

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Performed by Ensemble Volans at the University of Hamburg, Dec. 9 2017