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深度复古
传奇硬件模拟,蕴含深厚的复古灵魂

Deep Vintage 是一套传奇硬件模拟插件,能够让你沉浸在真正的模拟魔法中。它不仅仅追求真实的电路复制或特定的音质特点,而是模拟整个声音体验,重现数字世界中的复古“灵魂”。深度、光泽、低频饱和……每一个硬件音频的细微之处都等待着你去点燃,同时对CPU占用和延迟的要求极低。

APNN 2.0

基于三体科技(Three-Body Tech)专有的 APNN(音频处理神经网络)2.0 技术,Deep Vintage 仅通过声音进行学习,提供与原始硬件无可区分的听觉体验。

APNN 2.0 是一种专门用于模拟模拟硬件的神经网络。在训练过程中,APNN 2.0 和硬件会同时输入相同的音频,APNN 2.0 会学习硬件如何在波形和频谱维度上改变音频。这意味着经过良好训练的 APNN 2.0 实例能够捕捉到源硬件的动态特性和音色特点。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异。查看下方的演示,听听 APNN 2.0 如何逐步学习并复制硬件的声音。

当 APNN 2.0 实例完成训练后,我们会进行严格的人工测试,并做出调整,直到整个团队在 ABX 测试中失败。这样我们可以自豪地宣布:

在数字音频领域,没有任何东西比 Deep Vintage 更接近真实硬件。

Tape M

灵感来源于 70 年代德国的一款传奇双轨磁带机,Tape M 呈现出温暖且独特的音质,伴随着生动的低频表现。由于它的早期起源,它具有更丰富的色彩化和略为明显的抖动/颤动。当驱动稍微加大时,它会添加微妙的谐波失真,有助于在不使用过度压缩的情况下实现响度,使其成为混音或母带制作中的精致工具。

亮点

多重饱和、多级着色
借助 APNN 2.0 的强大功能,Deep Vintage 不仅模拟特定的频率响应或音色着色,还能模拟所有微妙的“硬件魔力”:动态、空气感、相位偏移、电子管电压衰减、变压器的“铁质音”等。无论是用于微妙的音色调整、适度的饱和,还是对整个音频的极端处理,其真实的表现将让你忘记它是数字模拟。

独立谐波控制
在真实硬件中,谐波量在某个旋钮设置下是固定的。而 Deep Vintage 引入了超现实的灵活性,允许谐波与其他音色特性独立控制。这让你可以在保持纯净音调的同时,调节出高驱动设置的音响力量。

低频饱和
音频变压器的“铁”声音——轻微增加的低频厚度和饱和度——是硬件音质的典型特征。Deep Vintage 不仅精确捕捉了这一点,还提供了开关功能,允许你在变压器版本和无变压器版本之间切换。无论你追求厚重还是清晰的音色,它总能以出色的质量呈现。

重新采样/超采样
几乎所有音频处理网络都在固定的采样率下运行,但我们通过优化网络实现了重新采样。Deep Vintage 中完全重新设计的重新采样算法确保了所有采样率下的一致精度和保真度,使模拟与采样率完全无关。此外,它支持高达 8 倍的超采样,有效消除了混叠问题。

EQ 联合训练
大多数神经网络只能捕捉硬件的离散状态,因此只能提供有限的 EQ 组合。然而,Deep Vintage 独特地通过额外的 EQ 模拟支持全连续的 EQ 调整。对于具有 EQ 的模型,“联合训练算法”同时学习硬件原型的饱和特性,并微调基于电路的预建 EQ 模块。这样你既能享受真实的硬件音质,又能完全自由地调节 EQ。

磁带抖动/颤动联合训练
抖动/颤动是由于磁带机传输系统机械不一致性引起的音高变化。抖动是指较慢且更明显的音高波动,而颤动则是较快的速度变化形式。

与 EQ 联合训练类似,APNN 2.0 使用物理建模的抖动/颤动模拟,并与神经网络联合训练。这不仅使神经网络训练的结果更加真实,还使模拟的抖动/颤动效果更接近原始硬件。

可调噪声底
Deep Vintage 系列模拟了硬件的固有噪声底,你可以根据需要调整其量。

“复古 DAW”模拟
该按钮灵感来自于 2000 年左右的一款经典 DAW 所引入的极其微小变化(小于 -140 dB)。尽管这些变化几乎不可察觉,我们也没有忽视它。你可以根据需要启用或禁用此功能。

低 CPU 占用率
无需昂贵的云端 GPU 集群 – Deep Vintage 像任何其他插件一样本地运行,并且对 CPU 的占用极低。你可以轻松地在每个轨道上插入它!

更多功能

  • 原生支持苹果芯片
  • 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 个采样点,约 0.6 毫秒 @ 44100 Hz

版本 1 修复:定时炸弹问题

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.Tape M

Inspired by a legendary 2-track tape machine from ’70s Germany, Tape M delivers a warm, distinctive character with a lively low end. Due to its earlier origins, it has a richer coloration and slightly more pronounced wow/flutter. When driven slightly hotter, it adds subtle harmonic distortion to help achieve loudness without excessive compression, making it a refined tool for mixdowns or mastering.

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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