This page includes of audio examples for the paper “Fully Conditioned and Low-latency Black-box Modeling of Analog Compression” by Riccardo Simionato and Stefano Fasciani, Department of Musicology, University of Oslo.
Associated code, dataset, and trained models are available on GitHub.
Examples are available for the following compressor models:
- CL 1B Dataset – Encoder Decoder Model (examples)
- LA-2A Dataset – Encoder Decoder Model (examples)
- PSP MicroComp Dataset – Encoder Decoder Model (examples)
- U-he Presswerk Dataset – Encoder Decoder Model (examples)
- Softube FET Dataset – Encoder Decoder Model (examples)
- CL 1B Dataset – Temporal Convolutional Network Model (examples)
Each example includes the following, the following audio and images are ???:
- Input Audio Signal
- Target Output Audio Signal (true output recorded from the device)
- Predicted Output Audio Signal (generated by the inference of the trained model)
- Waveform of Target and Predicted Output Audio Signal with respective RMS values
- Spectrograms of Target and Predicted Output Audio Signal
The title of the waveform plot details the compressor control parameters, valid for all devices except the LA-2A:
- at = attack time (ms)
- re = release time (s)
- ra = compression ratio (ra:1)
- th = threshold (dBu)
For the LA2A, the control parameters detailed in the title of the waveform plot are the following:
- M = mode (1 compression, 0 limit)
- p = peak reduction (dimensionless)
CL 1B Dataset – Encoder Decoder Model
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LA-2A Dataset – Encoder Decoder Model
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PSP MicroComp Dataset – Encoder Decoder Model
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U-he Presswerk Dataset – Encoder Decoder Model
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Softube FET Dataset – Encoder Decoder Model
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CL 1B Dataset – Temporal Convolutional Network Model
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CL 1B Dataset – Temporal Convolutional Network Model
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CL 1B Dataset – Temporal Convolutional Network Model
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