Finite-Length Markov Processes with Constraints

  title={Finite-Length Markov Processes with Constraints},
  author={François Pachet and Pierre Roy and Gabriele Barbieri},
Many systems use Markov models to generate finite-length sequences that imitate a given style. These systems often need to enforce specific control constraints on the sequences to generate. Unfortunately, control constraints are not compatible with Markov models, as they induce long-range dependencies that violate the Markov hypothesis of limited memory. Attempts to solve this issue using heuristic search do not give any guarantee on the nature and probability of the sequences generated. We… CONTINUE READING
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Showing 1-10 of 22 references

of 1st Int

  • A. Eigenfield, P. Pasquier. Realtime generation of harmonic progress Proc
  • Conf. on Computational Creativity, pages 16–25…
  • 2010
1 Excerpt

Algorithmic Composition

  • G. Nierhaus
  • Paradigms of Automated Music Generation…
  • 2009
1 Excerpt

Theory of Probability and Random Processes

  • L. Kolarov, Y. G. Sinai
  • Springer
  • 2007
1 Excerpt

A Modern Method for Guitar

  • W. Leavitt
  • Berklee Press, Boston, USA
  • 2005
1 Excerpt

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