对比黑箱与灰箱模型，提升音频效果建模的通用性与准确性。
Differentiable Black-box and Gray-box Modeling of Nonlinear Audio Effects
- 采用黑箱与灰箱架构对比建模非线性音频效果
- 在多种设备上验证模型性能，提出适配压缩器等新模型
- 发布首个可社区贡献的大规模音频效果数据集
音频效果广泛应用于音频与音乐内容创作的各个阶段。现有可微分音频效果建模方法多为黑箱或灰箱范式，且主要针对吉他放大器、过载、失真、模糊和压缩器等非线性效果。尽管已有众多网络架构被提出，但对当前技术状态仍缺乏系统理解，因多数研究仅针对单一类型效果且样本设备极少。本文通过在大量非线性音频效果上对比黑箱与灰箱架构，揭示最适合多种设备的建模方案。过程中引入时变灰箱模型，提出适用于压缩器、失真和模糊效果的新模型；发布大规模音频效果研究数据集ToneTwist AFx（https://github.com/mcomunita/tonetwist-afx-dataset），支持社区贡献；在多种指标下评估模型并开展广泛主观评测。代码与补充材料已开源。
原文摘要 · Abstract (English)
Audio effects are extensively used at every stage of audio and music content creation. The majority of differentiable audio effects modeling approaches fall into the black-box or gray-box paradigms; and most models have been proposed and applied to nonlinear effects like guitar amplifiers, overdrive, distortion, fuzz and compressor. Although a plethora of architectures have been introduced for the task at hand there is still lack of understanding on the state of the art, since most publications experiment with one type of nonlinear audio effect and a very small number of devices. In this work we aim to shed light on the audio effects modeling landscape by comparing black-box and gray-box architectures on a large number of nonlinear audio effects, identifying the most suitable for a wide range of devices. In the process, we also: introduce time-varying gray-box models and propose models for compressor, distortion and fuzz, publish a large dataset for audio effects research - ToneTwist AFx https://github.com/mcomunita/tonetwist-afx-dataset - that is also the first open to community contributions, evaluate models on a variety of metrics and conduct extensive subjective evaluation. Code https://github.com/mcomunita/nablafx and supplementary material https://github.com/mcomunita/nnlinafx-supp-material are also available.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。