I'm trying to write a program in Python that will take an input of a .wav (sound) file, and determine whether the user is saying "yes" or "no".
The issue is that the sound files are not always the same length.
I'm worried that with a static input dimension (i.e. 5 seconds of audio), I may have a sample that exceeds that dimension.
I recently read this paper written by Google's Deepmind, which uses sound, but I can't tell how they deal with this issue.
Any insights on how to allow my neural network to deal with a variable size input would be appreciated.