Fix and update codebase & pre-trained models with demo samples

1. Fix variance adaptor to make it work with all combinations of building block and variance type/level
2. Update pre-trained models with demo samples of LJSpeech and VCTK under "transformer_fs2" building block and "cwt" pitch conditioning
3. Share the result of ablation studies of comparing "transformer" vs. "transformer_fs2" paired among three types of pitch conditioning ("frame", "ph", and "cwt")

A lot of improvements with new features!

1. Prepare two different types of data pipeline in preprocessor to maximize unsupervised/supervised duration modelings

2. Adopt wavelet for pitch modeling & loss

3. Add fine-trained duration loss

4. Apply var_start_steps for better model convergence, especially under unsupervised duration modeling

5. Remove dependency of energy modeling on pitch variance

6. Add "transformer_fs2" building block, which is more close to the original FastSpeech2 paper

7. Add two types of prosody modeling methods

8. Loss camparison on validation set:

   • LJSpeech - blue: v0.1.1 / green: v0.2.0

   

   • VCTK - skyblue: v0.1.1 / orange: v0.2.0