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深度复古
传奇硬件模拟插件套件,拥有深厚的复古灵魂

Deep Vintage 是一套传奇硬件模拟插件,让你沉浸于真正的模拟魔力中。它不仅仅追求真实的电路复刻或特定的音色特质,而是模拟声音的全部,以在数字世界中再现复古的“灵魂”。深度、光泽、低频饱和度……硬件的每一个音频细节都为你准备好了,并且只需极少的 CPU 占用和延迟。

APNN 2.0
借助 Three-Body Tech 的专有 APNN(音频处理神经网络)2.0,Deep Vintage 通过仅仅对声音的学习,创造出与原始硬件难以区分的听觉体验。

APNN 2.0 是专为模拟模拟硬件设计的神经网络。在训练过程中,APNN 2.0 和硬件会输入相同的音频,APNN 2.0 将学习硬件如何在波形和频谱维度上改变音频。这意味着训练良好的 APNN 2.0 实例可以捕捉其源硬件的动态和音色特性。以下图表展示了,随着训练的进展,APNN 2.0 的波形和频谱响应偏差逐渐减少,最终变得与原始硬件无法区分。请查看下面的对应演示,听听 APNN 2.0 是如何逐步学习并复制硬件声音的。

在 APNN 2.0 实例完成训练后,我们会进行严格的人类测试,并进行调整,直到我们的整个团队无法通过 ABX 测试。这样我们才能自豪地宣布:

在数字音频领域,没有什么比 Deep Vintage 更接近真实硬件。

Nylon
Nylon 受一个独特而迷人的电路启发,提供两种着色模式:Yellow(黄色)模式提供闪亮的高频,Green(绿色)模式提供强劲的低频。两者都是“透明过载”效果,添加了微妙的谐波内容,比典型的饱和器更温和。

Yellow 模式主要在高频产生谐波,带来明亮、光滑的“光泽”。Green 模式则主要在低频添加饱和度,使低音、踢鼓或鼓组更有力量和攻击感。

亮点
多重饱和,多阶段着色
借助 APNN 2.0 的强大功能,Deep Vintage 不仅模拟了特定的频率响应或着色,还捕捉了所有细微的“硬件魔法”:动态、空气感、相移、管压衰减、变压器的“铁质音色”等。无论是用于细微的着色、适度的饱和,还是压碎整个音频,它的真实表现会让你忘记它是数字的。

独立的谐波控制
使用真实硬件时,谐波量会固定在一个旋钮设置下。然而,Deep Vintage 通过独立控制谐波量,与其他音色特性分开,实现了超现实的灵活性。这使你能够在保持干净音色的同时,拨动出高驱动设置的强大音效。

低频饱和
音频变压器的“铁质音色”——轻微添加的低频肥厚和饱和度——是硬件音色的精髓。Deep Vintage 不仅准确捕捉了这一点,还提供了切换此“铁质音色”的功能,让你可以在有或无变压器版本之间切换。无论你是追求厚重还是清晰的音色,它总能提供卓越的质量。

重采样/超采样
几乎所有的音频处理网络都在固定采样率下运行,但我们通过优化网络,使重采样成为可能。Deep Vintage 中全新设计的重采样算法确保了在所有采样率下的一致精度和保真度,使模拟完全不依赖采样率。此外,还支持高达 8 倍的超采样,彻底消除混叠问题。

EQ 联合训练
大多数神经网络只能捕捉硬件的离散状态,从而提供有限的 EQ 组合。然而,Deep Vintage 独特地支持通过额外的 EQ 模拟实现完全连续的 EQ 调整。对于带有 EQ 的模型,“联合训练算法”同时学习硬件原型的饱和特性,并根据电路微调预建的 EQ 模块。这让你在享受真实硬件音色的同时,拥有完全的 EQ 调整自由。

磁带的 Wow/Flutter 联合训练
Wow/Flutter 是磁带机由于磁带传输系统的机械不一致性而产生的音高变化。Wow 指的是较慢的、更明显的音高波动,而 Flutter 是更快的速度变化形式。

与 EQ 联合训练类似,APNN 2.0 使用物理建模的 wow/flutter 模拟,并与神经网络共同训练。这不仅使神经网络训练的结果听起来更加真实,还让建模的 wow/flutter 效果更加接近原始硬件。

可调噪声底
Deep Vintage 系列模拟了硬件固有的噪声底,并且你可以根据需要调整其量。

“复古 DAW”模拟
此按钮灵感来源于 2000 年左右经典 DAW 引入的极微小变化(小于 -140 dB)。虽然变化极其细微,但我们没有忽略它。你可以根据需要启用或禁用此功能。

低 CPU 占用
无需昂贵的云端 GPU 集群——Deep Vintage 本地运行,像其他插件一样,并且 CPU 占用极低。你可以轻松地在每条音轨上插入它!

更多功能

  • 原生支持 Apple Silicon
  • 撤销/重做
  • A/B 切换
  • 输入/输出电平表
  • 单声道模式
  • LR/MS 处理
  • 相位反转
  • GUI 缩放
  • 延迟:26 样本点,约 0.6ms @ 44100 Hz

修订版 1 修复时间炸弹。

Deep Vintage

Legendary Hardware Simulations with a Deep Vintage Soul

Deep Vintage is a suite of legendary hardware simulation plugins that will immerse you in real analog magic. Not merely pursuing bona fide circuit replication or specific tonal qualities, Deep Vintage simulates the entirety of sound to reproduce the vintage “soul” in a digital world. Depth, sheen, low-end saturation…every nuance of the hardware’s sonic spirit is ready for you to ignite, with minimal CPU usage and latency.

APNN 2.0

Trained with Three-Body Tech’s proprietary APNN (Audio Processing Neural Network) 2.0, Deep Vintage learns on sound, and sound alone, creating an indistinguishable listening experience from the original hardwares.

APNN 2.0 is a neural network specializes in simulating analog hardwares. During the training process, APNN 2.0 and the hardware will be inputted with the same audio, and APNN 2.0 will learn how the hardware changes the audio in both waveform and spectrum dimensions. This means that a well-trained APNN 2.0 instance can capture both the dynamic and tonal characteristics of its source hardware. The following diagram demonstrates how, as training progresses, APNN 2.0’s waveform and spectrum response deviation gradually decrease, eventually becoming indistinguishable from that of the original hardware. Check out the corresponding demos below to hear how APNN 2.0 progressively learns and replicates the sound of the hardware.

After an APNN 2.0 instance completes its training, we conduct rigorous human testing and make adjustments until our entire team fails the ABX test. This allows us to proudly announce:

in the realm of digital audio, nothing comes closer to real hardware than Deep Vintage.Nylon

Inspired by a unique and captivating circuit, Nylon offers two modes of coloration: Yellow for shimmering highs and Green for robust lows. Both are ‘Transparent Overdrive’ effects that add subtle harmonic content, gentler than typical saturators.

The Yellow mode mainly generates harmonics at high frequencies, giving a bright, polished ‘shine.’ The Green mode mainly adds saturation at low frequencies, making bass, kick drum, or drum bus more massive and aggressive.

HighlightsMultiplex Saturation, Multistage Coloration

With the power of APNN 2.0, Deep Vintage simulates not just specific frequency responses or coloration, but all the subtle ‘hardware mojos’: dynamics, airness, phase shifts, tube voltage sag, transformer’s “iron sound,“ and more. Whether for subtle coloration, moderate saturation, or crushing the entire audio, its authentic performance will make you forget it’s digital.

Independent Harmonics Control

With real hardware, the amount of harmonics is fixed at a given knob setting. However, Deep Vintage introduces surreal flexibility by allowing independent control over harmonics, separate from all other tonal characteristics. This lets you dial in the sonic power of high drive settings while maintaining the purity of a clean tone.

Low Frequency Saturation

The ‘iron’ sound of audio transformers – gently added low-end girth and saturation – epitomizes the sonic character of real hardware. Deep Vintage not only accurately captures this, but also provides you with the ability to toggle this ‘iron’ sound on or off, allowing you to switch between transformer or transformer-less versions. Whether you’re aiming for a thick or clear tone, it always delivers with exceptional quality.

Re-sampling/Up-sampling

Almost all audio processing networks operates in fixed sample rates, but we’ve made resampling possible by optimizing our networks. The completely redesigned resampling algorithm in Deep Vintage ensures consistent accuracy and fidelity across all sample rates, making the simulation fully sample rate agnostic. Additionally, up to 8x oversampling is supported, effectively eliminating any aliasing issues.

EQ Co-training

Most neural networks can only capture discrete states of the hardware, thus providing only limited EQ combinations. However, Deep Vintage uniquely supports fully continous EQ adjustment through extra EQ simulations. For models with EQ, the “co-training algorithm” simultaneously learns the hardware prototype’s saturation characteristics while fine-tuning a pre-modeled EQ module based on the circuit. This allows you to enjoy the authentic hardware sound while having complete freedom over EQ adjustment.

Tape Wow/Flutter Co-training

Wow/Flutter are pitch variations that occur in tape machines due to mechanical inconsistencies in the tape transport system. Wow refers to slower, more noticeable pitch fluctuations, while flutter on the other hand, is a faster form of speed variation.

Just like EQ co-training, APNN 2.0 uses a physically modeled wow/flutter simulation and co-trains it with the neural network. This not only makes the results of neural network training sound more authentic but also brings the modeled wow/flutter effect closer to the original hardware.

Adjustable Noise Floor

The Deep Vintage series simulates the hardware’s inherent noise floor, which you can adjust in amount as needed.

“Retro DAW” Simulation

This button is inspired by the extremely subtle changes (less than -140 dB) introduced by a classic DAW from around the year 2000. While the changes are infinitesimal, we didn’t overlook them. You can enable or disable this feature as needed.

Low CPU usage

No need for expensive cloud-based GPU clusters – Deep Vintage runs locally just like any other plugin, with extremely low CPU usage. You can easily insert it on every track!

More Features

  • Apple silicon native support
  • Undo/redo
  • A/B switching
  • Input/output level meter
  • Mono mode
  • LR/MS processing
  • Phase invert
  • GUI re-scaling

Latency

26 sample points, about 0.6ms at 44100 Hz

Rev1 Fix timebomb.

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