One thing that is a limitation here is the coverage of stft/fft in the backend.
stft maps to the internal _fft_r2c 2 and that in turn is implemented for only through MKL on the CPU 5.
I have an upcoming tutorial (in a week or two) for keyword recognition on ARM (but Raspberry rather than mobile) where I use the M5 model from the tutorial to avoid the need for spectrogram. It also has a few wrinkles.
For Linux on ARM you can always get numpy’s fft (like librosa does) but that might not be as straightforward on mobile.
Best regards
Thomas