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Interactive symbolic music analysis can now seamlessly combine predictive accuracy with user-driven refinement, transforming how musicians and analysts engage with music data.
Real-time music enhancement is achievable, but indiscriminate methods can actually degrade audio quality, revealing the critical need for tailored approaches.
The largest homogeneous Roman-numeral corpus ever created allows for direct note-for-note comparison across distinct analytical traditions, challenging existing standards in tonal harmony research.
Automatically transcribed music datasets can be cleaned and organized for performance analysis without relying on ground truth scores, using only structural similarities between performances.
Achieve improved music source restoration by cascading a BandSplit-RoFormer separator with HiFi++ GAN restorers, outperforming direct methods.
