I have audio samples with three classes :
100 audio samples : class 'A' 100 audio samples : class 'B' 100 audio samples : class 'C'
Class 'A' and
Class 'B' audio samples are recorded from one phone mic with same setting ( distance, volume etc ) but
class 'C' samples are from different phone mic, ( each audio sample is from different phone mic )
I am working on a ML classifier to classify all three audio classes. My question is if I downsample all the audio signals to one frequency (i.e 16 kHz)
- Will model still be biased because of different phone mic?
- What affects model will face because of different phone mic and what is the better solution for this problem other than downsampling to same frequency ?