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Prosody Loss
See original GitHub issueHi, I am adding your MDN prosody modeling code segment to my tacotron but I encountered several problems about the code segment about prosody modeling. First, the prosody loss is added into the total loss only after the prosody_loss_enable_steps but in the training steps before the prosody_loss_enable_steps the prosody representation is already added with the text encoding. Does it means in the training steps before the prosody_loss_enable_steps, the prosody representation is optimized without the prosody loss?
Second, in the training steps, the backward gradient of training prosody predictor should be acted like “stop gradient” but it seems little relevant code.
Thanks!
Issue Analytics
- State:
- Created a year ago
- Comments:7 (2 by maintainers)
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Hi,
I’m the author of this paper. My code for calculating the MDN loss is here with a small numerical stability trick:
Does that help?
The MDN loss (i.e. negative log-likelihood) can be negative value. However, in your log, it is almost 0 before becoming nan. I guess maybe you can check whether you calculate the likelihood correctly.