THREE-BODY TECH / NYLON download delivery

This plug-in, inspired by models with unique circuits, adds harmonic color to your sound. Available for download.

■Plug-in
■Vintage Transformer Simulation
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■Download Delivery
- Approximately 10 minutes after completing your purchase, an activation code will be delivered to your registered email address.
- Activate the code you received on the D2R page below and you will receive product installation information via email. (You can also view the information by clicking the email icon on the D2R page.)
D2R Page
*If you do not have a D2R Page account, please register by clicking ""Register here"" on the D2R Page.

- You can also view your D2R registration activation code by clicking ""Order Details"" in your Sound House My Page or Purchase History.
*It may take a few minutes for the information to be reflected in your purchase history.
- Click ""Support Information"" under ""Order Details"" to display activation information.
- For detailed installation/usage instructions, please contact the manufacturer.
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NYLON is inspired by models with unique and fascinating circuits and offers two coloration modes. ""Yellow"" mode adds brightness and ""sparkle"" to the high frequencies by generating harmonics in the high frequencies, while ""Green"" mode adds subtle saturation to the low mids to create powerful bass. Each mode enhances subtle resonances.

NYLON's ""Yellow"" and ""Green"" modes both belong to a type of effect known as ""transparent overdrive."" They add harmonic coloration to the audio signal, but are not as strong as a typical saturator.

Deep Vintage: AI Hardware Simulation Plug-in Series

The Deep Vintage series is a collection of plug-ins that harness the power of AI to simulate authentic hardware. These machines stand up to the Turing test of the human ear, faithfully capturing the true ""soul"" of vintage equipment.

Three-Body Tech's proprietary APNN (Audio Processing Neural Network), a machine learning technology specialized for simulating analog effect processors, ensures a listening experience that's closest to legendary hardware models while maintaining full real-time processing.

APNN (Audio Processing Neural Network) 2.0

Three-Body Tech has experimented with numerous emulation technologies, including physical modeling and convolution. Regardless of the technology used, THREE-BODY TECH's ultimate goal remains consistent: to reproduce the sound of real-world devices as faithfully as possible.

Trained by THREE-BODY TECH's proprietary APNN (Audio Processing Neural Network) 2.0, Deep Vintage delivers a listening experience indistinguishable from the original hardware.

APNN is a neural network optimized for audio processing, consisting of a large number of audio processing modules (EQ, compressor, overdrive, etc.). During the training process, the same audio is input to APNN 2.0 and the hardware, and APNN 2.0 learns how the hardware alters the input signal in both waveform and spectral dimensions. To capture the essence of the modeled hardware, it automatically adjusts its structure and parameters until the difference between the hardware and APNN 2.0 outputs is small. In other words, a fully trained APNN 2.0 instance is able to capture both the dynamic and tonal characteristics of the source hardware.

Ultimately, APNN achieves phase cancellation with an error of approximately -40dB to -75dB (depending on the hardware model). This exceptional level of error control, even surpassing variations between different production lots of the same hardware model, allows us to confidently say that APNN can ""fool"" the human ear.

After an instance of APNN 2.0 completed training, THREE-BODY TECH conducted rigorous human testing and continued tweaking until the entire team passed the ABX test. Nothing in a DAW is as close to the real hardware as a plug-in equipped with APNN 2.0.

■Features
Drive
Tweaks the drive effect of the current profile.

Presence
Adjusts the harmonic distortion and frequency response of the sound.

Deep
Boosts the low frequencies while affecting the distortion characteristics.

Link Mode Switch
Enables or disables link mode between the two channels; adjusting parameters on either channel affects the other channel.

Other Features
- Switchable Noise Simulation
Genuine hardware is inherently noisy. In fact, some vintage gear produces extremely high levels of noise. When an APNN learns from a hardware model, the network cannot be instructed to distinguish between sound and noise during the training process, so it captures all sounds, including noise. Fortunately, APNNs are not completely black boxes; you can control whether or not to generate noise after training. You can also disable/enable noise simulation in each DEEP VINTAGE product according to your preference. * Green AD AI does not have a 'Noise' button; this is because the noise level of the hardware models is low, making it unnecessary to disable it.
- Harmonics
Generates a certain amount of harmonics based on the modeled hardware. The Drive knob controls saturation by adjusting the input gain, while Harmonics directly edits the network model, forcing a reduction in the amount of generated harmonics. At 100% (default), the harmonic characteristics closely resemble those of the hardware model; lowering the value proportionally reduces the amount of harmonics (though due to the nature of the network architecture, it is not possible to completely bypass harmonics). This allows the plug-in to operate in a cleaner state, preserving mostly only the frequency response and dynamics.
- Oversampling
While Deep Vintage leverages the power of AI to closely resemble the hardware models that inspired it, digital audio still suffers from the curse of aliasing. Enabling 2x, 4x, 8x, and 16x oversampling can significantly reduce aliasing.
- Undo/Redo
- A/B Switching
- L/R/M/S Channel Monitoring
You can solo and monitor any of the left, right, middle, or side channels.
- Input/Output Level Meters
- Mono Mode
- LR/MS Processing
- Phase Inversion
- GUI Rescaling

Latency
Approximately 0.6 ms at 26 sample points and 44100 Hz

■ System Requirements
For the latest system requirements, please refer to the manufacturer's product page.