Comments (1)
Hi @ivancarapinha,
Sorry about the delay!
Yeah, the paper is very vague about the model details. You're correct that the one-hot representation is related to the 10-bit audio. Basically they apply mu-law companding to the original 16-bit audio. Then you form a one-hot representation for each sample where the 1 is at the index given by the mu-law companding. This is then fed into the autoregressive part of the model.
I used an embedding layer just to make the model a bit more efficient. The first operation in a GRU is a matrix multiplication with the input. So using a one-hot input picks out a column of the matrix (basically what an embedding layer does). I just separated out the embedding operation and used a smaller dimension which hopefully sped things up training a little. It should work fine if you go with the original approach though.
Hope that helps.
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Related Issues (20)
- 24kHz and 10 bit mu-law model HOT 2
- Question about preprocess.py HOT 1
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