Continuing the discussion from:
There could be value in ensuring that training can be done at other sample rates than 16kHz, but I’m unsure that resampling is the proper solution, to be honest.
I have added a variable(can be changed to a flag) which can be set to desired target SR. But won’t having a single sample rate(same as training and inference) improve convergence?
I’ve tested training models on different SR and inferencing on 16khz, and as expected, the model produces unacceptable results(WER, CER, LOSS and output put together). But the same model infers much better when using the same SR test files(Test results after training).
It does retain the original audio characteristics after resampling.
Do you think this would not be useful for training?