@MASTERSTHESIS{pgi2020003,
	author = "L. Devlin",
	supervisor = "D. Roussinov",
	title = "Using Recurrent Neural Networks to Generate Music",
	school = "Department of Computer and Information Sciences, University of Strathclyde",
	year = "2019",
	abstract = "This   project   focuses   on   the   application   of   Recurrent   Neural   Networks   (RNN)   to   the   {\"\i}{\neg}eld {\^A}  of   generative   symbolic   music.   The   following   paper   discusses   the   current   state   of   RNN {\^A}  music   generation   and   proposes   two   representations   for   compositions   with   a   shared {\^A}  underlying   data   structure.   Once   the   compositions   had   been   generated,   they   were {\^A}  compared   against   human-written   compositions   by   using   an   empirical   MIR   analysis {\^A}  system,   as   well   as   a   subjective   test   in   which   participants   offered   perceptual   responses {\^A}  to   the   compositions.   Overall,   while   the   system   was   able   to   produce   some   melodically {\^A}  pleasant   results,   it   failed   to   capture   the   long   term   structure   and   complexity   of   human {\^A}  compositions.",
}