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Acon Digital Extract Dialogue v1.5.0 [WiN, MacOSX]
On request Windows / Mac OSX WiN

Acon Digital Extract Dialogue v1.5.0 [WiN, MacOSX]

1 min read 6.4 MB
Extract:Dialogue is a plug-in that separates dialogue from common types of background noise such as wind, rustle, traffic, hum, clicks and pops. The algorithm works in real time and is based on deep learning. It has been trained on thousands of high-quality voice recordings and an equally extensive set of common noise sources. The extensive training enables the artificial intelligence to automatically distinguish dialogue from noise without user interaction. This makes Extract:Dialogue extremely easy to use – just add it to your dialogue bus and let it do its magic. Even though the noise reduction is fully automatic, the plug-in interface does offer simple controls to adjust the sensitivity of the noise detection and the maximum noise attenuation. The sensitivity can even be adjusted independently in up to three frequency bands. The maximum attenuation control is very handy when you only want to reduce the noise without removing it completely. All the parameters are fully automatable as you would expect.

Frequently Asked Questions

How can I access Acon Digital Extract Dialogue v1.5.0 [WiN, MacOSX]?

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What formats are included in Acon Digital Extract Dialogue v1.5.0 [WiN, MacOSX]?

This pack includes: multiple professional formats. All formats are industry-standard and compatible with major DAWs.

Is Acon Digital Extract Dialogue v1.5.0 [WiN, MacOSX] compatible with my DAW?

Yes, Acon Digital Extract Dialogue v1.5.0 [WiN, MacOSX] works with all major DAWs including FL Studio, Ableton Live, Logic Pro, and more.

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About Pluggi
Pluggi is the editorial curator behind Plugg Supply. The role combines resource discovery, catalog taxonomy, source review, and practical explanations for producers working with plugins, sample packs, Kontakt libraries, presets, and MIDI.
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Catalog records begin with source and availability data. A public verification badge is added only when its evidence has been recorded: documentation reviewed, source verified, archive verified, or a separately documented hands-on test.

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