Submitted by BackgroundPass2082 t3_1090y7r in deeplearning
(Audio newbie here) Hello, I have a noisy audio file (similar to the one of this video) and I need to separate as much as possible the voice of the commentators from the background noise. Which model do you recommend using? And is there any non-ML approach I should try? Thanks.
Check speechbrain on GitHub they have pretrained models
Check out the noisereduce library!!
Based on spectral gating, you can provide audio of the noise so it works better, works for stationary and non stationary noise.
I tried doing speech enhancement (denoising) using a SepFormer model (code here) and most of the talking is missing from the result. Probably in the considered case there's more background noise than usual :/
I'm trying it out. I'm curious to check the result - it's pretty resource intensive!
It is, you can specify the number of threads it uses tho. For realtime it doesn't work I guess but it's the best I have ever seen actually.
Thanks for letting me know! How do you specify the number of threads?
Hmmm ok sepformer usually works well.
njobs or so, it's in the documentation
Do you have any recommendations for something that can perform noise reduction in realtime?
I don't know if something good exists. If you have a strong gpu you could try denoising autoencoders but afaik it's only "real-time" when you get like a 10k gou and for this price you can also do it realtime with cpus.
Ah well. Thanks for the info!
For posterity: n_jobs, see here.
Use any VAD models?
VAD won't do it, since the speech and the noise overlap
parttimedeveloper t1_j3viq64 wrote
I guess you might want to do some Fourier transform, and do some tweaks in the frequency domain.