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."
It says it can remove car noises, but can it remove the audience laughter from the Red Green Show? This is a problem someone needs to solve!
Remember when Mozilla made a web browser? Pepperidge Farm remembers...
Only the State obtains its revenue by coercion. - Murray Rothbard
Perhaps the poster is suffering from multiple personality disorder, so he can be Edit or Dave. When the Edit personality is dominant, everything is checked for spelling, style, punctuation and grammar. When Dave is dominant, less so.
When the copyright term is "forever minus a day", live every day like it's the last.
I suggest piping in a few tracks by SPK, in particular "Emanation Machine R.Gie 1916", the first track from their 1981 release "Information Overload Unit".
https://www.youtube.com/watch?v=G9b89PFYZ5g
When my wife first heard it, she said it was like having your head stuck inside a running vacuum cleaner. Follow it up with some Throbbing Gristle, perhaps.
I tried to donate noise; using a mac under 10.12.6. Mic is working fine. Safari asks if it can use the mic. The record button stays in for 60 seconds. The playback produces nothing.
I have great noise sources, and would not mind contributing.
I've fallen off your lawn, and I can't get up.
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.
That link has only the source code. It does not include the training data set.
The submission link requires CC-0 attribution, which makes me hopeful that they plan to release the data freely. But I hunted all over the site and couldn't find either a link to the data or any comment about their plans for it going forward.
rage, rage against the dying of the light
Since when is ‘an’ equivalent to ‘all?’
It's the first time we try this. We'll look at the quality of the data we get (yes, noise quality!) and if it's sufficiently good/useful, then we'll also make it available. It might take some time to sort out the useful samples from the ones that aren't since some already have noise suppression applied by the OS or browser.
Opus: the Swiss army knife of audio codec
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
Millions of husbands just submitted the sound of their wife's voice.