FakeMusicCaps:用于检测和归因通过文本到音乐模型生成的合成音乐的数据集
Luca Comanducci1, Paolo Bestagini1, Stefano Tubaro1
1Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, 20133 Milano, Italy.
Journal of imaging
|July 25, 2025
概括
文本转音乐 (TTM) 模型产生了可信的音乐,但引发了版权问题. 本研究介绍了FakeMusicCaps用于检测和归因TTM生成的音频,以帮助音频法医.
科学领域:
- 人工智能的人工智能
- 音乐信息检索 音乐信息检索
- 音频法医学 音频法医学
背景情况:
- 文本转音乐 (TTM) 模型具有先进的自动音乐生成,产生高度可信的音频.
- 在商业和制作环境中越来越多地采用TTM,这引发了重要的版权和归因问题.
- 音频法医社区需要强大的方法来应对TTM产生的内容所带来的挑战.
研究的目的:
- 解决通过文本转音乐 (TTM) 模型生成的音乐的检测和归属问题.
- 引入一个新的数据集,FakeMusicCaps,用于评估TTM生成的音频.
- 评估TTM音频检测和归因方法的有效性.
主要方法:
- 开发FakeMusicCaps数据集,其中包括使用最先进的TTM技术再生的MusicCaps数据.
- 使用封闭式和开放式分类实验评估TTM生成的音频检测和归因.
- 对拟议的FakeMusicCaps数据集的分类性能进行分析.
主要成果:
- 最初的实验证明了检测和归因TTM生成的音频的可行性.
- FakeMusicCaps数据集为对TTM检测算法进行基准测试提供了宝贵的资源.
- 在封闭集和开放集分类场景之间观察到性能差异.
结论:
- 拟议的FakeMusicCaps数据集有助于对TTM音频法医学的研究.
- 有效地检测和归因TTM产生的音乐对于解决版权问题至关重要.
- 需要进一步的研究来完善TTM检测和归因方法,以适用于现实世界的应用.
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