Computer evaluation of musical timbre transfer on drum tracks

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dc.contributor.authorLee, Keon Ju
dc.contributor.supervisorTzanetakis, George
dc.date.accessioned2021-08-09T19:12:36Z
dc.date.available2021-08-09T19:12:36Z
dc.date.copyright2021en_US
dc.date.issued2021-08-09
dc.degree.departmentDepartment of Computer Scienceen_US
dc.degree.levelMaster of Science M.Sc.en_US
dc.description.abstractMusical timbre transfer is the task of re-rendering the musical content of a given source using the rendering style of a target sound. The source keeps its musical content, e.g., pitch, microtiming, orchestration, and syncopation. I specifically focus on the task of transferring the style of percussive patterns extracted from polyphonic audio using a MelGAN-VC model [57] by training acoustic properties for each genre. Evaluating audio style transfer is challenging and typically requires user studies. An analytical methodology based on supervised and unsupervised learning including visualization for evaluating musical timbre transfer is proposed. The proposed methodology is used to evaluate the MelGAN-VC model for musical timbre transfer of drum tracks. The method uses audio features to analyze results of the timbre transfer based on classification probability from Random Forest classifier. And K-means algorithm can classify unlabeled instances using audio features and style-transformed results are visualized by t-SNE dimensionality reduction technique, which is helpful for interpreting relations between musical genres and comparing results from the Random Forest classifier.en_US
dc.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/13221
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.subjectAudio Style Transferen_US
dc.subjectMusical Timbre Transferen_US
dc.subjectGANsen_US
dc.subjectComputer Evaluation of Audio Style Transferen_US
dc.subjectMethodologyen_US
dc.subjectMachine Learning Evaluation Pipelinesen_US
dc.subjectAI-assisted Music Analysisen_US
dc.subjectAudio Feature Engineeringen_US
dc.subjectComputer Evaluation of Autonomously Creative and Co-creative Music Systemsen_US
dc.titleComputer evaluation of musical timbre transfer on drum tracksen_US
dc.typeThesisen_US

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