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The rise of large language model AI generative tools has resulted in multiple AI music generators being made available to the public. But how good are they at tricking us into believing that they may be human-created? And can we manipulate the music produced to sound more human using production techniques like adding small human sound effects or introducing convolution reverbs? We ran four internet-based listening studies to try to answer these questions. AI-generated music was able to fool approximately half of the listeners into believing that it could be human generated. However, our interventions did not increase the likelihood of the music being labelled human-generated
Author (s): Collins, KC; Manji, Adel
Affiliation:
School of Information Technology, Carleton University, 1125 Colonel By Drive, Ottawa, ON K1S 5B6 Canada; School of Information Technology, Carleton University, 1125 Colonel By Drive, Ottawa, ON K1S 5B6 Canada
(See document for exact affiliation information.)
AES Convention: 156
Paper Number:203
Publication Date:
2024-06-06
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Permalink: https://aes2.org/publications/elibrary-page/?id=22549
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Collins, KC; Manji, Adel; 2024; Humanizing AI Generated Music Do Listeners Hear a Difference? [PDF]; School of Information Technology, Carleton University, 1125 Colonel By Drive, Ottawa, ON K1S 5B6 Canada; School of Information Technology, Carleton University, 1125 Colonel By Drive, Ottawa, ON K1S 5B6 Canada; Paper 203; Available from: https://aes2.org/publications/elibrary-page/?id=22549
Collins, KC; Manji, Adel; Humanizing AI Generated Music Do Listeners Hear a Difference? [PDF]; School of Information Technology, Carleton University, 1125 Colonel By Drive, Ottawa, ON K1S 5B6 Canada; School of Information Technology, Carleton University, 1125 Colonel By Drive, Ottawa, ON K1S 5B6 Canada; Paper 203; 2024 Available: https://aes2.org/publications/elibrary-page/?id=22549