Differentiable Feedback Delay Network for Colorless Reverberation
Gloria Dal Santo, Karolina Prawda, Sebastian J. Schlecht, and Vesa Välimäki
Companion page for a paper submitted to the 26th International Conference on Digital Audio Effects (DAFx 2023)
Abstract
Artificial reverberation algorithms often suffer from spectral coloration, usually in the form of metallic ringing, which impairs the perceived quality of sound. This paper proposes a method to reduce the coloration in the feedback delay network (FDN), a popular artificial reverberation algorithm. An optimization framework is employed entailing a differentiable FDN to learn a set of parameters decreasing coloration. The optimization objective is to minimize the spectral loss to obtain a flat magnitude response, with an additional temporal loss term to control the sparseness of the impulse response. The objective evaluation of the method shows a favorable narrower distribution of modal excitation while retaining the impulse response density. The subjective evaluation demonstrates that the proposed method lowers perceptual coloration of the late reverberation. It also shows that the suggested optimization improves sound quality for small FDN sizes. The method proposed in this work poses an improvement in designing accurate and high-quality artificial reverberation, at the same time offering computational savings.
Examples of impulse responses synthesized with the proposed Differentiable Feedback Delay Network (DiffFDN)
Exponentially Decaying FDN IR
Delay Set #1
Optimized (DiffFDN) |
Initialization |
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Delay Set #2
Optimized (DiffFDN) |
Initialization |
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Lossless FDN IR
Delay Set #1
Optimized (DiffFDN) |
Initialization |
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Delay Set #2
Optimized (DiffFDN) |
Initialization |
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