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You might be able to do this with independent component analysis (ICA). There is a block in sklearn, but you would have to write some Python.

Alternatively, you might look to see if the speakers are in separate channels (if recording is stereo). Then it would be really simple - just take one channel out and resave as mono!

If you have a sample I'd be curious to take a look - sounds like an interesting problem.

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ICA helps you separate a superposition of two or more signals. Assuming the speakers are not speaking at the same time, he might rather want to use speaker identification methods to find what parts to mute (e.g. train a binary classifier that operates a spectrogram of the signal).

Good point. I was thinking of two people speaking at the same time, but that would probably be hard to listen to :). Speaker dependent muting is a much more reasonable approach

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