Donate Your Noise To Xiph/Mozilla's Deep-Learning Noise Suppression Project (xiph.org)
Mozilla-backed researchers are working on a real-time noise suppression algorithm using a neural network -- and they want your noise! Long-time Slashdot reader jmv writes:
The Mozilla Research RRNoise project combines classic signal processing with deep learning, but it's small and fast. No expensive GPUs required -- it runs easily on a Raspberry Pi. The result is easier to tune and sounds better than traditional noise suppression systems (been there!). And you can help!
From the site: Click on this link to let us record one minute of noise from where you are... We're interested in noise from any environment where you might communicate using voice. That can be your office, your car, on the street, or anywhere you might use your phone or computer.
They claim it already sounds better than traditional noise suppression systems, and even though the code isn't optmized yet, "it already runs about 60x faster than real-time on an x86 CPU."
From the site: Click on this link to let us record one minute of noise from where you are... We're interested in noise from any environment where you might communicate using voice. That can be your office, your car, on the street, or anywhere you might use your phone or computer.
They claim it already sounds better than traditional noise suppression systems, and even though the code isn't optmized yet, "it already runs about 60x faster than real-time on an x86 CPU."
Remember when Mozilla made a web browser? Pepperidge Farm remembers...
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The entire project is on github.
I found this by going to the link in TFS.
I've fallen off your lawn, and I can't get up.
Now, training is a little trickier because I cannot share the data.
I cannot share the current data I'm using because it's copyrighted. Hence asking for people for help getting data that I can redistribute.
So weâ(TM)re supposed to just give jmv a bunch of data with no way to know how he is using it?
Yes, because I have such a track record for keeping things private.
Opus: the Swiss army knife of audio codec