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Computer Science > Sound

arXiv:2105.09046 (cs)
[Submitted on 19 May 2021 (v1), last revised 9 Jun 2021 (this version, v3)]

Title:Music Generation using Three-layered LSTM

Authors:Vaishali Ingale, Anush Mohan, Divit Adlakha, Krishan Kumar, Mohit Gupta
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Abstract: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.
Subjects: Sound (cs.SD); Artificial Intelligence (cs.AI); Machine Learning (cs.LG); Audio and Speech Processing (eess.AS)
Cite as: arXiv:2105.09046 [cs.SD]
  (or arXiv:2105.09046v3 [cs.SD] for this version)
  https://doi.org/10.48550/arXiv.2105.09046

Submission history

From: Vaishali Ingale [view email]
[v1] Wed, 19 May 2021 10:27:58 UTC (303 KB)
[v2] Thu, 27 May 2021 16:09:44 UTC (303 KB)
[v3] Wed, 9 Jun 2021 08:15:19 UTC (210 KB)
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