How to process a voice input in Keras that is not one of the two speaker outputs?
It is not a simple matter. You need a lot more training examples and to do some tests.
You COULD try to train something to be you-and-your-friend vs all, but it won't be that easy and (again) you will need lots of examples.
It's very broad as a question, there are a few different approaches and i'm not sure Keras and neural networks are the correct answer for this specific task.
I'm trying to create a speaker recognition with a neural network using Keras and also the Fourier transformation to process the voice samples. The voice samples are me and my friend saying 'eeeee' for 3 seconds. Now the problem is if we give the neural network an input of someone else doing that ('ee' for 3 seconds), it still gives an output that indicates that it's  100% one of us. I output data using softmax so it gives about [1, 0] for my friend and [0, 1] for me. Sometimes it's like [0.95, 0.05]. 
It's working well except for if we input the data from another person like I said, it still gives like [1,0] although I would expect it to give something like [0.6, 0.4] because it's another voice. Now I have also tried using 2 features of MFCC but it doesn't seem to work either. Would making a third output and train it with random samples work (I myself don't really think so because it can't train for all different inputs)? Or how can I try to face this issue otherwise? I've been struggling with this issue for quite a while now so any help would be much appreciated!