Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Music Generation using Three-layered LSTM   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.

11
The categories of this paper are: hep-lat
0
The categories of this paper are: hep-ph
30
The categories of this paper are: q-alg
5
The categories of this paper are: gr-qc
37
The categories of this paper are: supr-con
2
The categories of this paper are: math
14
The categories of this paper are: math-ph
3
The categories of this paper are: physics
22
The categories of this paper are: chao-dyn
18
The categories of this paper are: econ
26
The categories of this paper are: bayes-an
31
The categories of this paper are: ao-sci
29
The categories of this paper are: funct-an
8
The categories of this paper are: hep-ex
32
The categories of this paper are: atom-ph
27
The categories of this paper are: comp-gas