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深度复古
具有深度复古灵魂的传奇硬件模拟
Deep Vintage 是一套传奇的硬件模拟插件,让您沉浸在真正的模拟魔法中。它不仅仅追求真实的电路复刻或特定的音色品质,而是模拟声音的整体,重现数字世界中的复古“灵魂”。深度、光泽、低频饱和度……硬件声音的每个细微之处都已为您准备好,且占用极少的CPU资源和低延迟。
APNN 2.0
Deep Vintage 采用 Three-Body Tech 的专有 APNN(音频处理神经网络)2.0 进行训练,专注于声音本身,创造出与原始硬件无法区分的听觉体验。
APNN 2.0 是专门用于模拟模拟硬件的神经网络。在训练过程中,APNN 2.0 和硬件将接收到相同的音频输入,学习硬件在波形和频谱维度上如何改变音频。这意味着经过充分训练的 APNN 2.0 实例能够捕捉其源硬件的动态和音色特性。下方的图表展示了,随着训练的进展,APNN 2.0 的波形和频谱响应偏差逐渐减少,最终与原始硬件难以区分。您可以通过下方的演示,听到 APNN 2.0 如何逐步学习并复制硬件的声音。
当 APNN 2.0 完成训练后,我们会进行严格的人工测试,并进行调整,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,Deep Vintage 最接近真实的硬件。
Transformer X
除了电子管外,硬件电路中最具音色决定性的组件是变压器,尤其是带有标志性“铁声”的复古变压器。受一款使用复古美式变压器的定制“彩盒”启发,Transformer X 能轻松为您的声音增添温暖、厚实感和低频力量。
亮点
多路饱和、多级着色
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,还重现了所有微妙的“硬件魔法”:动态、空气感、相移、管电压下垂、变压器的“铁声”等。无论是微妙的着色、适度的饱和还是彻底压缩音频,其真实表现都能让您忘记这是数字模拟。
独立谐波控制
在真实的硬件中,给定旋钮设置下的谐波量是固定的。然而,Deep Vintage 引入了超现实的灵活性,允许您独立控制谐波,与其他音色特性分开。这让您可以在保持纯净音色的同时,调整高驱动设置的音响力量。
低频饱和
音频变压器的“铁声”——轻微增加的低频厚度和饱和感——是硬件音色的典型特征。Deep Vintage 不仅精确捕捉了这一点,还为您提供了打开或关闭“铁声”的选项,让您在变压器或无变压器版本之间自由切换。不论是追求厚重还是清晰的音色,它始终以卓越的质量呈现。
重采样/上采样
几乎所有的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采样。Deep Vintage 完全重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,使模拟完全与采样率无关。此外,它支持高达 8 倍的上采样,有效消除了任何混叠问题。
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 模拟支持完全连续的 EQ 调整。对于具有 EQ 的模型,“联合训练算法”在学习硬件原型的饱和特性时,同时微调基于电路的预建 EQ 模块。这让您在享受真实硬件音色的同时,拥有对 EQ 调整的完全自由。
磁带 Wow/Flutter 联合训练
Wow/Flutter 是磁带机中由于磁带传输系统的机械不一致性引起的音高变化。Wow 是指较慢、更明显的音高波动,而 Flutter 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 wow/flutter 模拟,并与神经网络进行联合训练。这不仅使神经网络训练的结果更加真实,还使建模的 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,您可以根据需要调整其量。
“复古 DAW” 模拟
该按钮的灵感来自大约 2000 年左右的一款经典 DAW 所引入的极其微小的变化(小于 -140 dB)。虽然这些变化极其细微,但我们没有忽视它。您可以根据需要启用或禁用此功能。
低 CPU 使用率
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,占用极少的 CPU 资源。您可以轻松地将其插入每个轨道!
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 缩放调整
- 延迟:26 采样点,约 0.6 毫秒(44100 Hz)
Rev1 修复了定时炸弹问题。
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.Transformer X
Other than electron tubes, the most tone-defining component in hardware circuits is the transformer – especially vintage transformers with their signature ‘iron sound’. Inspired by a custom ‘color box’ utilizing a vintage US transformer, Transformer X can easily add warmth, body, and low-end girth to your sound.
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.