4(Feed-Forward)A-2A: an emulator plugin for LA-2A optical compressor

4A-2A is a VST plugin that emulates the LA-2A optical compressor using a feed-forward digital compressor. The accompanying abstract, Emulating LA-2A Optical Compressor With a Feed-Forward Digital Compressor Using the Newton-Raphson Method, is accepted at DMRN+19.

We implement a mapping function $\mathbb{R} \to \mathbb{R}^5$ that maps the peak reduction of the LA-2A to the five parameters of the feed-forward compressor. The mapping function is learnt using the Newton-Raphson method on the SignalTrain dataset.

Interface

The plugin comes with six sliders and one button, which are:

1. Threshold - The threshold of the compressor in dB.
2. Ratio - The ratio of the compressor (1 to 20).
3. Attack - The attack time of the compressor in ms (0.1 to 100).
4. Release - The release time of the compressor in ms (100 to 1000).
5. Make-up - The make-up gain of the compressor in dB.
6. Peak Reduction - The emulated peak reduction of the LA-2A (40 to 100). This slider controls the other five sliders and overrides their values.
7. Comp./Limit. - The mode of the compressor. When the button is changed, sliders 1-5 are also changed based on the peak reduction.

Installation

The pre-built VST3 binaries for Windows and macOS can be found in the releases. One can also build the plugin from source using the Projucer project file.

Training code

Coming soon.

Evaluation

We calculate the Error-to-Signal Ratio (ESR) of the plugin using the SignalTrain dataset. The ESR is calculated as $\frac{|\hat{\bf x} - \bf x|^2}{|\bf x|^2}$, and the results are shown below. We are planning to add more evaluation results and compare to other compressor emulators in the future.

Peak Reduction	4A-2A
40	8.4298%
45	8.0200%
50	7.6414%
55	7.3810%
60	7.1569%
65	7.0386%
70	6.6416%
75	6.5745%
80	6.6973%
85	6.7294%
90	8.1090%
95	9.2127%
100	10.1523%

Citation

If you use this plugin in your research, please cite it as:

@inproceedings{yu2024emulating,
  title={Emulating LA-2A Optical Compressor With a Feed-Forward Digital Compressor Using the Newton-Raphson Method},
  author={Chin-Yun Yu and György Fazekas},
  booktitle={Proceedings of the Digital Music Research Network Workshop},
  year={2024}
}