Please use this identifier to cite or link to this item:
https://rda.sliit.lk/handle/123456789/1711
Title: | Thuryalankara: Artificial Intelligence Based Audio Plugin For Sri Lankan Percussion Instruments |
Authors: | Fernando, P. D. C Fernando, B. A. N Wanaguru, I. U Perera, M. A. P. A Buddhika, T Kodagoda, N Ganegoda, D |
Keywords: | Thuryalankara Artificial Intelligence Audio Plugin Sri Lankan Percussion Instruments |
Issue Date: | 1-Dec-2021 |
Publisher: | IEEE |
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. |
Series/Report no.: | 2021 6th International Conference on Information Technology Research (ICITR);Pages 1-6 |
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. |
URI: | http://rda.sliit.lk/handle/123456789/1711 |
ISBN: | 978-1-6654-2000-6 |
Appears in Collections: | Department of Computer Science and Software Engineering-Scopes Research Papers - Dept of Computer Science and Software Engineering Research Papers - IEEE Research Papers - SLIIT Staff Publications |
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Thuryalankara_Artificial_Intelligence_Based_Audio_Plugin_For_Sri_Lankan_Percussion_Instruments.pdf Until 2050-12-31 | 643.19 kB | Adobe PDF | View/Open Request a copy |
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