Hi all 
I want to construct a 3 channel “image” from audio recordings to feed into a CNN. The three channels would be:

STFT i.e. standard spectrogram
Mel-spectrogram
“Fingerprint” which is a sparse matrix representing the strongest frequencies in the standard spectrogram. This is modelled after the old Shazam algorithm.

The problem is that each of these three visual representations of audio data has different shapes given the same audio.
Question 1
Can I construct a 3 channel image without resizing the channels to equal dimensions?
Question 2
If not, is there any reason to fear resizing the images to match each other? My concern is that the meaning of the data in each will be corrupted.
Question 3:
Would it perhaps be better to create an ensemble of three different CNN’s rather than try squeeze all these different shaped data through a single model?
Thanks in advance to you audio/visual experts!