The app is truly a drag and drop no frills easy as pie to use app that requires no real configuration and can even handle batches of files at once. Im a youtuber and I ocasionally edit the audio file from my church for a podcast and I was immediately floored when I ran both of the spoken audio styles through Hush. I absolutely love how simple this is to use. Your data stays private, and the app is yours forever.Īpple Silicon (M1 or M2) strongly recommended, eGPUs and Intel CPUs also supported.Īny questions or feedback? Drop me an email at Owl Neural networks with this much power usually require a server - along with hefty usage or subscription fees. It’s also blazing fast, processing an hour-long podcast in a matter of minutes.

On M1 and M2 Macs, Hush uses the energy-efficient Neural Engine, leaving your chassis cool, your fans off, and your CPU free for other tasks.

Choose an output folder and let Hush clean up all your audio in one go. Hush accepts individual audio files or whole batches, making short work of dialogue stems, voiceover auditions, or audiobook chapters. Hush eliminates them with surgical precision, saving you hours of manual editing. Most noise reduction algorithms struggle to remove transient sounds like chirping birds, barking dogs, or honking horns. Crank up the dial to absorb every trace of reverb, or mix in some dry signal for a more natural sound. Reduce room reflections and comb filtering - from untreated condos to massive auditoriums. Restore audio from imperfect environments and produce studio-quality recordings wherever you are. Hush filters out broadband sounds like ventilation, appliances, traffic, and wind. The result preserves all the nuance of the original signal, as if it were recorded in a well-treated studio.Ĭheck out the audio demo at. Powered by machine learning, Hush removes background noise and room reflections from recorded speech - without audible artifacts or loss of clarity.

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