Institutional-Repository, University of Moratuwa.  

Thuryalankara: artificial intelligence based audio plugin for Sri Lankan percussion instruments

Show simple item record

dc.contributor.author Fernando, PDC
dc.contributor.author Fernando, BAN
dc.contributor.author Wanaguru, IU
dc.contributor.author Perera, MAPA
dc.contributor.author Buddhika, T
dc.contributor.author Kodagoda, N
dc.contributor.author Ganegoda, D
dc.contributor.editor Ganegoda, GU
dc.contributor.editor Mahadewa, KT
dc.date.accessioned 2022-11-09T09:04:38Z
dc.date.available 2022-11-09T09:04:38Z
dc.date.issued 2021-12
dc.identifier.citation P. D. C. Fernando et al., "Thuryalankara: Artificial Intelligence Based Audio Plugin For Sri Lankan Percussion Instruments," 2021 6th International Conference on Information Technology Research (ICITR), 2021, pp. 1-6, doi: 10.1109/ICITR54349.2021.9657391. en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/19445
dc.description.abstract Sri Lankan music is yet to prove its musical prowess by incorporating artificial intelligence tools, therefore, this research introduces a novel invention, an automated audio plugin for music producers, so the process of creating, mixing, mastering, and producing music is easier. To achieve this, the research introduces a Variational AutoEncoder (VAE) machine learning model to create and generate music, an artificial intelligence (AI) system that can automate the mastering process. This research also introduces an innovative component, a virtual instrumentation tool using MIDI technology for the Sri Lankan percussion instruments that allow users to play the instrument virtually using a MIDI keyboard, and alongside it, a preset beat generator that automatically maintain tempo consistency. Thuryalankara was able to receive a collective average of 80% accuracy rate exceeding the predicted accuracy rate of 65% from the software benchmarking test and the physical survey conducted with music producers. Finally, with the inclusion of powerful tools like this, the ultimate objective of this research is to take the Sri Lankan instruments to the international level where any producer from little to plenty experience is able to use this plugin to enhance their musical production. en_US
dc.language.iso en en_US
dc.publisher Faculty of Information Technology, University of Moratuwa. en_US
dc.relation.uri https://ieeexplore.ieee.org/document/9657391 en_US
dc.subject Audio plugin en_US
dc.subject Sri Lankan music en_US
dc.subject Machine Learning en_US
dc.subject Virtual Instrumentation en_US
dc.subject Mix and Master en_US
dc.title Thuryalankara: artificial intelligence based audio plugin for Sri Lankan percussion instruments en_US
dc.type Conference-Full-text en_US
dc.identifier.faculty IT en_US
dc.identifier.department Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa. en_US
dc.identifier.year 2021 en_US
dc.identifier.conference 6th International Conference in Information Technology Research 2021 en_US
dc.identifier.place Moratuwa, Sri Lanka en_US
dc.identifier.proceeding Proceedings of the 6th International Conference in Information Technology Research 2021 en_US
dc.identifier.doi doi: 10.1109/ICITR54349.2021.9657391. en_US


Files in this item

This item appears in the following Collection(s)

  • ICITR - 2021 [39]
    International Conference on Information Technology Research (ICITR)

Show simple item record