I want to normalize my data prior to a deep neural network model (DNN). It was recommended to me to use real mean square (RMS) normalization for audio, though I am not sure this is the best for a DNN. I am using MFCC features to represent the data.
Is RMS a good method? If so, how do I choose a good RMS value to normalize with respect to that value? Is there a rule of thumb?