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FDNR Screenshot

If you are looking for a high-quality reverb plugin but don’t want to break the bank, you might want to check out FDNR (Feedback Delay Network Reverberator).

It is a free, open-source plugin that is similar to Valhalla reverbs (like VintageVerb and Room) but comes with a much more feature-rich engine under a modern, flat design. Best of all, it is totally free!

One of the coolest features is that you can share your reverb settings with your co-producers or friends simply by sharing a .json file. This makes collaboration and preset sharing incredibly easy.

You can download the plugin from the Releases Page.


What is FDNR?

Feedback Delay Network Reverberator (FDNR) is an open-source, modular reverb engine offering high-fidelity algorithms inspired by classic space reverberators. It features deep modulation, multiple reverb modes, and VST3 compatibility.

Technical Deep Dive: Inside the FDN

At its core, FDNR relies on a Feedback Delay Network (FDN). Unlike simple comb filter reverbs, an FDN uses a unitary matrix to mix the outputs of multiple delay lines before feeding them back into the inputs. This creates a dense, colorless tail that builds up echo density rapidly over time.

The signal flow can be visualized as follows:

  1. Input: The audio signal is distributed to $N$ parallel delay lines.
  2. Delay Lines: Each line delays the signal by a specific amount (determined by the mode/prime numbers).
  3. Absorption Filters: Low-pass and high-pass filters in the feedback loop simulate air absorption and material damping.
  4. Feedback Matrix: A Householder or Hadamard matrix mixes the delay line outputs. This mixing is crucial for maximizing echo density and preventing metallic ringing.
  5. Output: The tapped signals are summed to create the wet reverb signal.
graph LR Input[Input Signal] --> Split(( )) Split --> D1[Delay Line 1] Split --> D2[Delay Line 2] Split --> D3[Delay Line 3] Split --> D4[Delay Line 4] D1 --> Filter1[Absorption Filter] D2 --> Filter2[Absorption Filter] D3 --> Filter3[Absorption Filter] D4 --> Filter4[Absorption Filter] Filter1 --> Matrix[Feedback Matrix] Filter2 --> Matrix Filter3 --> Matrix Filter4 --> Matrix Matrix --> |Feedback| D1 Matrix --> |Feedback| D2 Matrix --> |Feedback| D3 Matrix --> |Feedback| D4 Matrix --> Output((Sum Output))

Echo Density & Impulse Response

One of the key characteristics of an FDN is its rapidly increasing echo density. In the early reflections, you can hear distinct echoes (represented by the spikes in the graph below). As time progresses, the feedback matrix smears these echoes into a smooth, diffuse tail.

xychart-beta title "Conceptual Impulse Response of an FDN" x-axis "Time (ms)" [0, 50, 100, 150, 200, 250, 300] y-axis "Amplitude" [0, 1] line [1.0, 0.8, 0.4, 0.2, 0.1, 0.05, 0.02] bar [1.0, 0.6, 0.5, 0.3, 0.2, 0.1, 0.05]

Note: The bar chart represents early reflections, while the line approximates the energy decay envelope (RT60).

Features

Controls

Algorithms (Modes)

FDNR offers a wide variety of algorithms to suit different needs:

Installation

For Users

  1. Download the latest Release for your operating system (Windows, Mac, or Linux) from the Releases page.
  2. Unzip the downloaded .zip file.
  3. VST3 Plugin:
    • Find the FDNR.vst3 file (or folder).
    • Copy it to your system’s VST3 directory:
      • Windows: C:\Program Files\Common Files\VST3\
      • Mac: /Library/Audio/Plug-Ins/VST3/
      • Linux: ~/.vst3/ or /usr/lib/vst3/ (or your DAW’s VST3 folder)
  4. Standalone Application (Optional):
    • Find the FDNR executable (or app bundle).
    • You can run this directly or copy it to your Applications folder.

If the plugin doesn’t appear in your host:


References

If you are interested in the math behind FDNs, check out these resources:

  1. Jot, J.-M., & Chaigne, A. (1991). Digital delay networks for designing artificial reverberators. Audio Engineering Society Convention 90.
  2. Smith, J. O. (online). Physical Audio Signal Processing: Feedback Delay Networks (FDN). ccrma.stanford.edu
  3. Schlecht, S. J., & Habets, E. A. P. (2019). Modal Decomposition of Feedback Delay Networks. IEEE Transactions on Signal Processing.

Check out the source code on GitHub.