Multilayer Perceptron for Symbolic Indonesian Music Generation

Arik Kurniawati, Yoyon Kusnendar Suprapto, Eko Mulyanto Yuniarno

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

Music is one of the arts of a beauty that cannot be separated from humans. But not all humans can create beautiful music. Therefore, this paper's objective was to design a creative aid to musical composition with minimum human intervention. This paper purpose builds generative music using Multilayer Perceptron (MLP) Neural Networks as architecture to create predicted chord as musical accompaniment. In contrast, the previous work in music generation has mainly been focused on creating subsequent next music patterns. Using the symbolic Indonesian music dataset (note and chord) to train the models. Finally, we predict sequential chords using symbolic notes from the data test. Later, the generated Chords by Neural Network is compared with the original music Indonesian.

Original languageEnglish
Title of host publicationProceedings - 2020 International Seminar on Intelligent Technology and Its Application
Subtitle of host publicationHumanification of Reliable Intelligent Systems, ISITIA 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages228-233
Number of pages6
ISBN (Electronic)9781728174136
DOIs
Publication statusPublished - Jul 2020
Externally publishedYes
Event2020 International Seminar on Intelligent Technology and Its Application, ISITIA 2020 - Virtual, Online, Indonesia
Duration: 22 Jul 202023 Jul 2020

Publication series

NameProceedings - 2020 International Seminar on Intelligent Technology and Its Application: Humanification of Reliable Intelligent Systems, ISITIA 2020

Conference

Conference2020 International Seminar on Intelligent Technology and Its Application, ISITIA 2020
Country/TerritoryIndonesia
CityVirtual, Online
Period22/07/2023/07/20

Keywords

  • multilayer perceptron
  • music generation
  • symbolic

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