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dc.contributor.authorVanka, Sen_US
dc.contributor.authorSafi, Men_US
dc.contributor.authorRolland, J-Ben_US
dc.contributor.authorFazekas, Gen_US
dc.contributor.authorAES Europe Convention 2023en_US
dc.date.accessioned2023-04-28T09:21:49Z
dc.date.available2023-05-05en_US
dc.date.issued2023-05-02en_US
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/86042
dc.description.abstractThe integration of artificial intelligence (AI) technology in the music industry is driving a significant change in the way music is being composed, produced and mixed. This study investigates the current state of AI in the mixing workflows and its adoption by different user groups. Through semi-structured interviews, a questionnaire-based study, and analyzing web forums, the study confirms three user groups comprising amateurs, pro-ams, and professionals. Our findings show that while AI mixing tools can simplify the process and provide decent results for amateurs, pro-ams seek precise control and customization options, while professionals desire control and customization options in addition to assistive and collaborative technologies. The study provides strategies for designing effective AI mixing tools for different user groups and outlines future directions.en_US
dc.titleAdoption of AI Technology in the Music Mixing Workflow: An Investigationen_US
dc.typeConference Proceeding
dc.rights.holder© 2023 Audio Engineering Society
pubs.notesNot knownen_US
pubs.publication-statusAccepteden_US
dcterms.dateAccepted2023-05-05en_US
rioxxterms.funderDefault funderen_US
rioxxterms.identifier.projectDefault projecten_US
qmul.funderUKRI Centre for Doctoral Training in Artificial Intelligence and Music::Engineering and Physical Sciences Research Councilen_US


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