Title :
Creating melodies with evolving recurrent neural networks
Author :
Chen, Chun-Chi J. ; Miikkulainen, Risto
Author_Institution :
Texas Univ., Austin, TX, USA
Abstract :
Music composition is a domain well-suited for evolutionary reinforcement learning. Instead of applying explicit composition rules, a neural network is used to generate melodies. An evolutionary algorithm is used to find a neural network that maximizes the chance of generating good melodies. Composition rules on tonality and rhythm are used as a fitness function for the evolution. We observe that the model learns to generate melodies according to these rules with interesting variations
Keywords :
evolutionary computation; learning (artificial intelligence); music; recurrent neural nets; evolutionary reinforcement learning; melody creation; music composition; recurrent neural network evolution; Analytical models; Evolutionary computation; Learning; Music; Neural networks; Psychoacoustic models; Psychology; Recurrent neural networks; Rhythm; Writing;
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7044-9
DOI :
10.1109/IJCNN.2001.938515
