This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Music Generation with Markov Models
July-September 2011 (vol. 18 no. 3)
pp. 78-85
Walter Schulze, Stellenbosch University
Brink van der Merwe, Stellenbosch University

By using music written in a certain style as training data, parameters can be calculated for Markov chains and hidden Markov models to capture the musical style of the training data as mathematical models.

1. J. Högberg, Wind in the Willows, tech. report UMINF 05.13, Umeå Univ., 2005; http://www.cs.umu.se/~johannawillow/.
2. W. Chai and B. Vercoe, "Folk Music Classification Using Hidden Markov Models," Proc. Int'l Conf. Artificial Intelligence, 2001.
3. J. Triviño-Rodriguez and R. Morales-Bueno, "Using Multiattribute Prediction Suffix Graphs to Predict and Generate Music," Computer Music, vol. 25, no. 3, 2001, pp. 62-79.
4. F. Pachet, "The Continuator: Musical Interaction with Style," New Music Research, vol. 32, no. 3, 2003, pp. 333-341.
5. D. Ron, Y. Singer, and N. Tishby, "The Power of Amnesia: Learning Probabilistic Automata with Variable Memory Length," Machine Learning, vol. 25, no. 2, 1996, pp. 117-149.
6. L. Schwardt, Efficient Mixed-Order Hidden Markov Model Inference, doctoral dissertation, Univ. of Stellenbosch, 2007.
7. P. Dupont, F. Denis, and Y. Esposito, "Links between Probabilistic Automata and Hidden Markov Models: Probability Distributions, Learning Models and Induction Algorithms," Pattern Recognition, vol. 38, no. 9, 2005, pp. 1349-1371.
8. D. Jurafsky and J.H. Martin, Speech and Language Processing, 2nd ed., Prentice Hall, 2008.
9. W. Schulze, "A Formal Language Theory Approach to Music Generation," master's thesis, Univ. of Stellenbosch, 2009.
1. D. Conklin and C. Anagnostopoulou, "Representation and Discovery of Multiple Viewpoint Patterns," Proc. Int'l Computer Music Conf., Int'l Computer Music Assoc., 2001, pp. 479-485.
2. S. Dubnov et al., "Using Machine-Learning Methods for Musical Style Modeling," Computer, vol. 36, no. 10, 2003, pp. 73-80.
3. J. Triviño-Rodriguez and R. Morales-Bueno, "Using Multiattribute Prediction Suffix Graphs to Predict and Generate Music," Computer Music, vol. 25, no. 3, 2001, pp. 62-79.
4. F. Pachet, "The Continuator: Musical Interaction with Style," New Music Research, vol. 32, no. 3, 2003, pp. 333-341.
5. A. Moray and C.K.I. Williams, "Harmonising Chorales by Probabilistic Inference," Advances in Neural Information Processing Systems, vol. 17, L.K. Saul, Y. Weiss, and L. Bottou eds., MIT Press, 2005, pp. 25-32.
6. I. Simon, D. Morris, and S. Basu, "Mysong: Automatic Accompaniment Generation for Vocal Melodies," Proc. SIGCHI Conf. Human Factors in Computing Systems, ACM Press, 2008, pp. 725-734.

Index Terms:
algorithmic music composition, hidden Markov models, probabilistic automata
Citation:
Walter Schulze, Brink van der Merwe, "Music Generation with Markov Models," IEEE Multimedia, vol. 18, no. 3, pp. 78-85, July-Sept. 2011, doi:10.1109/MMUL.2010.44
Usage of this product signifies your acceptance of the Terms of Use.