Comments (3)
Thanks for the comment. So if i understand correctly you train the model to identify the speaker on a 200ms random chunk of the audio. While testing you take multiple such chunks and classify all of them and vote on the best ones? So in conclusion your model cannot handle variable length signals for now?
Also, during generating training batches, you seem to be multiplying an amplitude factor randomly chosen from (0.8, 1.2) to the signal. Is there any rationale behind this?
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