首个系统评估音乐编辑中上下文保持能力的框架，助力更可靠的音乐处理。
Evaluating Music Context Preservation: A Multi-facet Framework for Music Editing Systems
- 构建多维度音乐属性评估框架，覆盖四类关键音乐特征。
- 通过客观测试与真人实验验证指标有效性，结果可靠。
- 可诊断现有编辑系统优劣，适合音乐生成与处理研究者使用。
音乐编辑在现代音乐制作中至关重要，广泛应用于影视、广播和游戏开发。近期进展使音色迁移、乐器替换和风格转换等任务成为可能。然而，多数工作忽视了编辑过程中应保持不变的音乐特征，我们将其定义为音乐上下文保持（MuseCP）。尽管部分研究考虑该问题，其评估协议和度量方法仍不全面。为此，我们提出首个MuseCP评估框架MuseCPEval，涵盖四类音乐属性，采用细粒度且定制化的度量指标以捕捉音乐属性的细微变化。客观验证与人类评估均证明这些指标的有效性。对多种音乐编辑系统的案例研究展示了其作为测试平台和诊断工具的实际价值，揭示了现有系统的优势与局限。我们希望本框架能为开发具备强MuseCP能力的高效可靠音乐编辑策略提供实用指导。
原文摘要 · Abstract (English)
Music editing plays a vital role in modern music production, with applications in film, broadcasting, and game development. Recent advances in music editing systems have enabled diverse editing tasks such as timbre transfer, instrument substitution, and genre transformation. However, many existing works overlook evaluating their ability to preserve musical facets that should remain unchanged during editing, which we define as Music Context Preservation (MuseCP). While some studies do consider MuseCP, their evaluation protocols and metrics are not comprehensive. To address this, we introduce the first MuseCP evaluation framework, MuseCPEval, that covers four categories of music facets with fine-grained and well-tailored metrics to capture nuanced changes in music attributes. Objective validation and a human study demonstrate the effectiveness of these metrics. Moreover, the case studies on diverse music editing systems illustrate the practical utility of these metrics as a testbed and diagnostic tool, providing insights into the strengths and limitations of existing systems. We hope our metrics and findings can offer practical guidance for developing more effective and reliable music editing strategies with strong MuseCP capability
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