The research side of "minimum modifications required" is with not quite there yet [0]. Audio source separation for now is probably the way to go (see other chil

The research side of "minimum modifications required" is with not quite there yet [0]. Audio source separation for now is probably the way to go (see other child comment). Although I imagine it would encounter similar problems with "over the air" type environments. Black box transfers require large, audibly noticeable modifications. see "Transfer attacks against YouTube’s Content ID" audio example in [0]. Most work has focused on speech recognition, so see final appendix in [1], the authors of which are currently looking at the problem in more detail (stay tuned for results). Also, over-the-air attacks require a lot more modification than attacks against image classifiers [2]. A lot of recent work (for voice at least) has found signal processing tricks are simple and efficient ways to deal with it [3]. But these untargeted attacks always run the risk of copyright detection flagging it as a different song instead of "not copyrighted". So, basically, more research is required to get to the Fawkes "for audio" [4]. As an aside: I would not want to be "that guy" who invented the technology to defeat audio copyright detection systems. I think copyright is a good thing and would only work on something like that to help improve a given system. This specific issue should be handled by through some form of legal proceeding. [0]: https://www.cs.umd.edu/~tomg/projects/copyrightattack/ https://www.cs.umd.edu/~tomg/projects/copyrightattack/ [1]: https://arxiv.org/abs/2007.06622 https://arxiv.org/abs/2007.06622 [2]: https://arxiv.org/abs/1908.01551v1 https://arxiv.org/abs/1908.01551v1 [3]: https://arxiv.org/abs/1910.05262 https://arxiv.org/abs/1910.05262 [4]: https://sandlab.cs.uchicago.edu/fawkes/ https://sandlab.cs.uchicago.edu/fawkes/ Edit: phone went mad and wouldn't let me type things.