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深度复古
传奇硬件模拟,赋予深邃复古灵魂

Deep Vintage 是一套传奇硬件模拟插件,让你沉浸在真实的模拟音频魔法中。它不仅追求真实的电路复制或特定音色的品质,而是完整地模拟声音,以在数字世界中再现复古的“灵魂”。无论是深度、光泽、低频饱和感,硬件音频的每个细节都随时可以展现,同时占用极少的 CPU 资源和低延迟。

APNN 2.0
Deep Vintage 使用 Three-Body Tech 的专有 APNN(音频处理神经网络)2.0 进行训练,只通过声音进行学习,创造出与原始硬件无可区分的听觉体验。

APNN 2.0 是一种专注于模拟模拟硬件的神经网络。在训练过程中,APNN 2.0 和硬件将输入相同的音频,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,经过充分训练的 APNN 2.0 实例可以捕捉到源硬件的动态和音色特征。下图展示了随着训练的进行,APNN 2.0 的波形和频谱响应偏差逐渐减少,最终与原始硬件无异。你可以通过下面的演示听到 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,我们进行严格的人工测试,直到整个团队在 ABX 测试中都无法分辨出与真实硬件的区别。因此,我们自豪地宣布:

在数字音频领域,Deep Vintage 是最接近真实硬件的选择。

US Rack
US Rack 灵感来源于传奇的“US”风格通道条,集成了前置放大器、线路驱动器和知名 EQ,提供高度音乐性和丰富的模拟音色,同时保持非凡的灵活性。

亮点

多级饱和,多重色彩
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音色,还捕捉了所有微妙的“硬件灵性”:动态、空气感、相位偏移、电子管电压下垂、变压器的“铁声”等。无论是轻微着色、中度饱和还是完全压缩音频,Deep Vintage 的真实表现让你完全忘记它是数字插件。

独立谐波控制
在真实硬件中,谐波的数量在特定旋钮设置下是固定的。然而,Deep Vintage 提供了令人惊叹的灵活性,允许你独立控制谐波,与其他音色特性分离。这让你可以在保持干净音色的同时,调出高驱动设置下的声音力量。

低频饱和
音频变压器的“铁声”——低频的轻微厚重和饱和感——是硬件音色的标志性特征。Deep Vintage 不仅准确地捕捉到了这一点,还允许你切换这种“铁声”,使你可以在带变压器和无变压器版本之间自由选择。无论你想要厚重还是清晰的音色,它总能以卓越的质量呈现。

重新采样/超采样
几乎所有音频处理网络都在固定采样率下运行,但我们通过优化网络使重新采样成为可能。Deep Vintage 全新设计的重新采样算法确保了在所有采样率下的精确度和保真度,使其模拟完全与采样率无关。此外,还支持最高 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,因此提供的 EQ 组合有限。然而,Deep Vintage 通过额外的 EQ 模拟,独特地支持完全连续的 EQ 调整。对于带有 EQ 的模型,“联合训练算法”可以同时学习硬件的饱和特性,并基于电路对预先建模的 EQ 模块进行精调。这样,你既能享受真实硬件的音效,还能完全自由地调整 EQ。

磁带 Wow/Flutter 联合训练
Wow/Flutter 是磁带机传输系统机械不一致性导致的音高波动。Wow 指的是较慢、更明显的音高波动,而 Flutter 是速度较快的音高变化。

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。这不仅让神经网络的训练结果更真实,还使模拟的 Wow/Flutter 效果更接近原始硬件。

可调噪声底
Deep Vintage 系列模拟了硬件固有的噪声底,并允许根据需要调整噪声量。

“复古 DAW”模拟
此按钮的灵感来自于 2000 年左右的经典 DAW 所引入的极其微小的变化(小于 -140 dB)。虽然这些变化微乎其微,但我们并没有忽略它们。你可以根据需要启用或禁用该功能。

低 CPU 占用
无需昂贵的基于云的 GPU 集群——Deep Vintage 像其他插件一样在本地运行,极少占用 CPU 资源。你可以轻松地将其插入每个轨道上使用!

更多功能

  • 原生支持 Apple Silicon
  • 撤销/重做功能
  • 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,大约 0.6 毫秒(在 44100 Hz 下)

Rev1 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.US Rack

Inspired by a legendary ‘US’ style channel strip that features a preamp, a line-driver, and a renowned EQ, US Rack delivers a highly musical and rich analog sound while maintaining extraordinary flexibility.

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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