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Deep Vintage
传奇硬件模拟,蕴含深厚复古灵魂
Deep Vintage 是一套传奇硬件模拟插件,带你沉浸于真正的模拟音质之中。它不仅追求真实的电路再现或特定的音质特性,更是通过全面的声音模拟再现复古“灵魂”于数字世界中。无论是深度、光泽还是低频饱和度……硬件的每一个细微音质都在这里复活,同时具备极低的 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 通过声音而非电路图进行学习,从而带来与原始硬件无法区分的听觉体验。
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 和硬件将输入相同的音频数据,学习硬件在波形和频谱维度上对音频的变化。因此,训练良好的 APNN 2.0 实例能捕捉到其原始硬件的动态和音色特征。下图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小,最终与原始硬件无法区分。请查看下方对应的演示,聆听 APNN 2.0 如何逐步学习和复制硬件的声音特性。
一旦 APNN 2.0 实例完成训练,我们会进行严格的人工测试并调整,直到整个团队无法通过 ABX 测试。这让我们自豪地宣布:
在数字音频领域,没有任何技术比 Deep Vintage 更接近真实硬件。
Brit 73
灵感来自地球上最具传奇色彩的前级放大器。这款 A 类晶体管前级放大器带有 EQ,完美展现了声音的美感,提供无与伦比的清晰度、光泽和穿透力。
亮点
多重饱和、复合染色
凭借 APNN 2.0 的强大性能,Deep Vintage 不仅模拟特定的频率响应或音色,还再现了所有细微的“硬件魔力”:动态、空气感、相位偏移、电子管电压衰减、变压器的“铁音”等。无论是轻微染色、中等饱和,还是对音频的完全粉碎,其真实的表现会让你忘记它是数字的。
独立谐波控制
在真实硬件中,谐波的量在特定旋钮设置下是固定的。然而,Deep Vintage 提供了超凡的灵活性,允许独立控制谐波,与其他音色特性分离。这使你能够在保持干净音色的同时,调整到高驱动设置的声音能量。
低频饱和
音频变压器的“铁音”——低频的厚重感和饱和度——是硬件声音的精髓所在。Deep Vintage 不仅精确捕捉到这一特性,还提供开启或关闭该“铁音”效果的选项,使你可以在带有变压器或不带变压器的版本之间切换。不论是追求厚实还是清晰的音色,它总能提供卓越的品质。
重采样/上采样
几乎所有音频处理网络都运行在固定采样率上,但我们通过优化网络实现了重采样。Deep Vintage 中全新设计的重采样算法确保了在所有采样率下的精度一致性,模拟完全采样率无关。此外,支持高达 8 倍的过采样,有效消除任何混叠问题。
EQ 联合训练
大多数神经网络只能捕捉硬件的离散状态,因而只能提供有限的 EQ 组合。然而,Deep Vintage 通过额外的 EQ 模拟支持完全连续的 EQ 调整。对于带 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模 EQ 模块,使你在享受真实硬件声音的同时,可以完全自由地调整 EQ。
磁带 Wow/Flutter 联合训练
Wow/Flutter 是磁带机因传送系统机械不稳定而产生的音高变化。Wow 是较慢且明显的音高波动,而 Flutter 则是较快的速度变化。
与 EQ 联合训练类似,APNN 2.0 使用物理建模的 Wow/Flutter 模拟,并与神经网络进行联合训练。这不仅让神经网络的训练结果更加逼真,还使模拟的 Wow/Flutter 效果更加贴近原始硬件。
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
此按钮受启发于 2000 年左右的一款经典 DAW 所引入的极细微变化(低于 -140 dB)。尽管变化极小,但我们并未忽略。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 本地运行如同其他插件一般,CPU 占用极低。你可以轻松地在每个音轨上使用它!
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 重缩放
延迟
26 样本点,在 44100 Hz 下约为 0.6ms
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.Brit 73
Inspired by the most legendary preamp on this planet. This class-A, transistor preamp with EQ epitomizes the beauty of sound, offering unparalleled clarity, sheen, and bite.
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