Closed Aditya-shahh closed 3 years ago
I also found that the mean-variance normalization does not seem to be very rigorous. The normal way to do it is to perform (x - mean)/std. Variance in this repository is estimated instead of accurate calculation
Hey, Thank you for sharing possible mistakes I might have made :)
@Aditya-shahh: I'm not sure that it would make sense to pad here as all test audio clips are longer than a second. @whmrtm: I'm not sure what you are saying here. We calculated the mean and variance and saved it in a separate file and then load it to standardize the data.
Please let me know if I'm missing something.
closing this for now
Hello,
In
examples/speaker_identification/test_TIMIT.py
at line 84, we have:data_tmp[:,:,0] = log_standardize(data_tmp[:,:,0])
Before applying log standardization, the signal needs to be padded; similar to how it is performed in the
data_generator.py
file at line 138So here before line 84 in
test_TIMIT.py
, please add the code:data_tmp = pad_spec(data_tmp)
Let me know if it's identified correctly.
Thank you