DocumentCode
2836199
Title
Composing Music with BPTT and LSTM Networks: Comparing Learning and Generalization Aspects
Author
Correa, Debora C. ; Saito, Josê H. ; Abib, Sandra
Author_Institution
Abib Univ. Fed. de Sao Carlos, Sao Paolo
fYear
2008
fDate
16-18 July 2008
Firstpage
95
Lastpage
100
Abstract
Many researchers have used neural networks on music composition. The architecture of the network and the representation of the training data have influence on the results. We propose to compare BPTT and LSTM networks in musical composition task with two different pitch representations. We present the learning algorithms of both networks and the results obtained in the composition of new melodies.
Keywords
learning (artificial intelligence); music; neural nets; BPTT networks; LSTM networks; learning algorithm; music composition; neural networks; pitch representation; Artificial neural networks; Biological neural networks; Computer networks; Conferences; Data mining; Frequency; Image converters; Neurons; Pattern analysis; Training data; Learning Algorithms; Music Composition; Neural Networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Science and Engineering Workshops, 2008. CSEWORKSHOPS '08. 11th IEEE International Conference on
Conference_Location
San Paulo
Print_ISBN
978-0-7695-3257-8
Type
conf
DOI
10.1109/CSEW.2008.69
Filename
4625046
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