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https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4910| Title: | Audio Source Separation and Automatic Music Transcription on Specific Instruments |
| Authors: | Akarawita, S. U. |
| Issue Date: | 16-Jun-2025 |
| Abstract: | Abstract Imagine listeningtoasymphonywhereviolins,pianos,anddrumsblendseamlessly, creating arichmusicalexperience.Butwhatifwecouldisolatejusttheviolinfromthat mix, capturingitsmelodieswithprecision?Thisistheessenceofaudiosourceseparation, whichisknownasextractingindividualinstrumentsfromacomplexmusicalpiece. Atthesametime,musictranscriptionhaslongbeenataskrequiringhumanexpertise. Turninganaudiorecordingintomusicalnotes(MIDI)hastraditionallybeenamanual process,demandingatrainedear.However,withadvancesinmachinelearning,wenow havethepotentialtoautomatethisprocess,makingmusicmoreaccessible,editable,and analyzable. This researchfocusesondevelopingmachinelearningmodelsthatcanseparatecertain instrumentalaudiofrompolyphonicrecordingsandconvertitintoMIDI.Bybridgingthe fields ofaudiosourceseparationandautomaticmusictranscription(AMT),weaimto push theboundariesofhowmachinesunderstandandprocessmusic. |
| URI: | https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4910 |
| Appears in Collections: | 2025 |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 20000073 - S. U. Akarawita - Mr. AKARAWITA S.U.. Copy pdf.pdf | 4.69 MB | Adobe PDF | View/Open |
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