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arXiv AI By Yash Vishe, Eric Xue, Xunyi Jiang, Zachary Novack, Junda Wu, Julian McAuley, Xin Xu

Evaluating Music Context Preservation: A Multi-facet Framework for Music Editing Systems

Read the original on arXiv AI →

The paper introduces MuseCPEval, the first comprehensive framework for assessing Music Context Preservation (MuseCP) in music editing systems. It defines four categories of music facets and provides fine‑grained metrics to detect subtle changes during editing tasks such as timbre transfer, instrument substitution, and genre transformation. The authors validate the metrics objectively and through a human study, and demonstrate their practical use in evaluating diverse editing systems, offering insights into each system’s strengths and limitations.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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