Music Melody Prediction using Hypernetworks)

Human can follow melody which he has not listened to before. Especially human predict next melody better if they are familiar with the genre of the song. We assume that melody is time series data. Recently hypernetworks have been researched for classification and time series problems. In this paper, we use evolutionary hypernetwork models (EHNs) for predicting difference of pitch. Evolutionary hypernetwork model can represent the corpus of melody and predict unseen melody partly.

[1]  Byoung-Tak Zhang,et al.  Evolutionary hypernetworks for learning to generate music from examples , 2009, 2009 IEEE International Conference on Fuzzy Systems.

[2]  Byoung-Tak Zhang,et al.  Evolving hypernetwork models of binary time series for forecasting price movements on stock markets , 2009, 2009 IEEE Congress on Evolutionary Computation.

[3]  Petri Toiviainen,et al.  MIDI toolbox : MATLAB tools for music research , 2004 .

[4]  Byoung-Tak Zhang,et al.  Evolving hypernetworks for pattern classification , 2007, 2007 IEEE Congress on Evolutionary Computation.

[5]  Jean-François Paiement,et al.  Predictive models for music , 2009, Connect. Sci..