%0 Journal Article
%T Polyphonic Music Generation by Modeling Temporal Dependencies Using a RNN-DBN
%A Kratarth Goel
%A Raunaq Vohra
%A J. K. Sahoo
%J Computer Science
%D 2014
%I arXiv
%R 10.1007/978-3-319-11179-7_28
%X In this paper, we propose a generic technique to model temporal dependencies and sequences using a combination of a recurrent neural network and a Deep Belief Network. Our technique, RNN-DBN, is an amalgamation of the memory state of the RNN that allows it to provide temporal information and a multi-layer DBN that helps in high level representation of the data. This makes RNN-DBNs ideal for sequence generation. Further, the use of a DBN in conjunction with the RNN makes this model capable of significantly more complex data representation than an RBM. We apply this technique to the task of polyphonic music generation.
%U http://arxiv.org/abs/1412.7927v1