  This paper explores the idea of utilising Long Short-Term Memory neural
networks (LSTMNN) for the generation of musical sequences in ABC notation. The
proposed approach takes ABC notations from the Nottingham dataset and encodes
it to be fed as input for the neural networks. The primary objective is to
input the neural networks with an arbitrary note, let the network process and
augment a sequence based on the note until a good piece of music is produced.
Multiple calibrations have been done to amend the parameters of the network for
optimal generation. The output is assessed on the basis of rhythm, harmony, and
grammar accuracy.
