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I am looking for a way to remove a known signal, A, of fixed length, from an unknown audio stream, B, when signal A can be mixed into signal B at any point in time. I may be mistaking but converting signal A to the frequency domain and performing an STFT where the window is approximately the size of the data buffer of signal B then subtracting these wouldn't work because the amount of signal A that may be contained in signal B is unknown.

Simply, i want to do live noise removal, when the noise is known. What are some methods of approaching this?

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  • $\begingroup$ Maybe cross correlation might be a better option. $\endgroup$
    – fibonatic
    Commented Jun 2, 2018 at 10:23
  • $\begingroup$ So, I'll check how similar the signals are using cross correlation and then based off that, perform spectral subtraction? $\endgroup$
    – Will D
    Commented Jun 2, 2018 at 10:34
  • $\begingroup$ It will tell you at what time A and B are most similar, and I think that peak also can tell you the magnitude. $\endgroup$
    – fibonatic
    Commented Jun 2, 2018 at 11:34
  • $\begingroup$ I would suggest to also try this NMF approach. It depends on a type of the signals but it should generally work well. $\endgroup$
    – jojeck ♦
    Commented Jun 3, 2018 at 7:14
  • $\begingroup$ With regards to that approach, will that work if you are using an audio stream and only have a snippit of the data that you want to denoise in a buffer, or does it only work on two known sources? $\endgroup$
    – Will D
    Commented Jun 3, 2018 at 11:32

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