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This demo presents the RNNoise project, showing how deep learning can be applied to noise suppression. The main idea is to combine classic signal processing with deep learning to create a real-time noise suppression algorithm that's small and fast. No expensive GPUs required — it runs easily on a Raspberry Pi. The result is much simpler (easier to tune) and sounds better than traditional noise suppression systems (been there!).

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Possible alternative uses for this algorithm ?

Date: 2017-09-29 07:49 am (UTC)
From: (Anonymous)
Long time ago I used to make amateur remixes, and one tricky part was to isolate vocals from the remixed track. To do that I was using the noise removal tool: select a part of the track without vocals, run a spectral analysis on it and then substract the result to the whole track. Most of the time the result was terribly mangled, but sometimes I got something usable.

Your demo got me thinking: if I want to remove something very specific from one track instead of learning a generalized filter, can I train this model with a smaller dataset, like a few seconds from that track?
From: (Anonymous)
Hi Jean Marc,

There was a 1.6 million $ Indigogo project about Snoring noise suppression device that went bust.
https://www.indiegogo.com/projects/silent-partner-quiets-snoring-noise-like-magic-sleep/x/14463062#/

Do you think you could help them?

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