I am trying to create a neural network that performs speaker recognition. I would like to be able to serve it such that it takes streaming audio - i.e. I want to perform partial recognition on 100ms frames and then calculate an average at the end.
I would like to know which of the following two forseeable options is the best.
- Training the network on audio clips of 100ms
- Using audio clips of arbitrary lengths and feeding subsequent 100ms segments into some sort of recurrent network. I was thinking that similar to text analysis, maintaining some state information could be useful in real time speaker identification.
Does anyone have some guidance in this regard? Thanks.