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Absolute values of some variance parameters are two large. Normalize them to the similar scale may improve the performance and benifits fine-tuning.
Sometimes linear normalization has trade-offs between precision and range. For example, delta_pitch needs more precision around 0, but also needs a wider range than the current default ±8 keys in some situations.
TODO
New option to normalize variance parameters to (-1, 1) before they are embedded into the model
Multiple types of normalization: linear, tanh, etc.
Generalize configuration schemas of all parameters
The text was updated successfully, but these errors were encountered:
Motivation
delta_pitch
needs more precision around 0, but also needs a wider range than the current default ±8 keys in some situations.TODO
The text was updated successfully, but these errors were encountered: