Description
DeRoom Pro
DeRoom Pro is a Machine-Learning based reverb removal audio plug-in built for professional use. An artificial neural network has been trained on many different room scenarios in order to be able to separate direct sound from reflection components. The real-time processing scheme provides instantaneous feedback while changing parameters and allows seamless integration into your workflow.
Accurate Speech Restoration
All signal components which result from sub?optimal recording conditions are automatically detected and removed. The de?reverberation can significantly improve the perceived speech quality and intelligibility. No matter if recorded in an acoustically untreated recording room or even in a large church, DeRoom Pro will fix your recording.
Automatic Room Size Estimation
The DeRoom Pro algorithm automatically estimates the optimal room-size settings. During the training phase the neural network has listened to a great variety of different room conditions and can now automatically apply the required filtering.
Second GenerationT
he second generation of DeRoom Pro features an improved filtering algorithm which provides a higher accuracy when detecting room reflections. Especially noticeable when using with recordings in larger rooms with long reverb tails.
Visualization
Choose between two different visualization modes to directly see how DeRoom Pro is affecting the signal. While the Waveform view shows the broadband energy, the Spectrogram view allows you to observe different frequency components.
Features
- increase the quality and intelligibility of your dialogue recordings
- speed up your post-production workflow with automatic processing
- parametrise for three separate frequency bands
- adjust the parameters by only listening to the reverb content
- real-time processing
- compatible with all major Digital-Audio-Workstations (ProTools,Cubase,Reaper,Ableton,Nuendo,Logic and more)
- compatible sample-rates: 44.1kHz, 48kHz, 88.2khz, 96kHz, 192kHz
Tech Specs
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Mac:
Cpu: Dual-Core 2Ghz
Ram: 2
Version: 10.12 or later
Additional_requirements: Universal binary with native M1-support
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Windows:
Cpu: Dual-Core 2Ghz
Ram: 2
Version: 7 or later