The Mozilla Research RRNoise project shows how to apply deep learning to noise suppression. It 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!).
You can improve RNNoise by donating your noise to science. 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. The more realistic noise we have, the better the models we can build and the better the output.
Read in depth about the RNNoise project.
About Jean-Marc Valin
Jean-Marc Valin has a B.S., M.S., and PhD in Electrical Engineering from the University of Sherbrooke. He is the primary author of the Speex codec and one of the main authors of the Opus codec. His expertise includes speech and audio coding, speech recognition, echo cancellation, and other audio-related topics. He is currently employed by Mozilla to work on next-generation multimedia codecs.