Adoption of AI Technology in the Music Mixing Workflow: An Investigation
April 06, 2023 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Soumya Sai Vanka, Maryam Safi, Jean-Baptiste Rolland, George Fazekas
arXiv ID
2304.03407
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.AI,
cs.SD,
eess.AS
Citations
11
Venue
arXiv.org
Last Checked
4 months ago
Abstract
The 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.
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