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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.
Author (s): Sai Vanka, Soumya; Safi, Maryam; Rolland, Jean-Baptiste; Fazekas, György
Affiliation:
Queen Mary University of London, London, UK; Steinberg Media Technologies GmbH, Hamburg, Germany; Steinberg Media Technologies GmbH, Hamburg, Germany; Queen Mary University of London, London, UK
(See document for exact affiliation information.)
AES Convention: 154
Paper Number:10653
Publication Date:
2023-05-06
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Session subject:
Mixing
Permalink: https://aes2.org/publications/elibrary-page/?id=22060
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Sai Vanka, Soumya; Safi, Maryam; Rolland, Jean-Baptiste; Fazekas, György; 2023; Adoption of AI Technology in Music Mixing Workflow: An Investigation [PDF]; Queen Mary University of London, London, UK; Steinberg Media Technologies GmbH, Hamburg, Germany; Steinberg Media Technologies GmbH, Hamburg, Germany; Queen Mary University of London, London, UK; Paper 10653; Available from: https://aes2.org/publications/elibrary-page/?id=22060
Sai Vanka, Soumya; Safi, Maryam; Rolland, Jean-Baptiste; Fazekas, György; Adoption of AI Technology in Music Mixing Workflow: An Investigation [PDF]; Queen Mary University of London, London, UK; Steinberg Media Technologies GmbH, Hamburg, Germany; Steinberg Media Technologies GmbH, Hamburg, Germany; Queen Mary University of London, London, UK; Paper 10653; 2023 Available: https://aes2.org/publications/elibrary-page/?id=22060
@article{sai2023adoption,
author={sai vanka soumya and safi maryam and rolland jean-baptiste and fazekas györgy},
journal={journal of the audio engineering society},
title={adoption of ai technology in music mixing workflow: an investigation},
year={2023},
number={10653},
month={may},}