How can you perform echo cancellation on features of audio signals?
well, while applying a room impulse response to audio (which is what echoes are) is a linear operation on the time-domain signal, it's generally not on features.
So, you're looking to find a non-linear mapping of a somewhat high-dimensional feature vector space to a &quot;cleaned up&quot; feature vector space with some well-known metric on how well that mapping performs as cleanup....
That sounds exactly like the kind of job that neural networks are good at. And that's not a coincidence: When you look under the mathematical hood of all your ML algorithms, there's the Universal Approximation Theorem that says that a NN that's sufficiently large can represent any non-linear mapping.
So, really, that's a hard problem to do analytically, and it's thoroughly reasonable to assume that &quot;echo removal on MFCC features&quot; can most sensibly be done with a Neural network, most likely even the same that you directly train to classify your audio signals.