MoonInTheRiver / MoonInTheRiver/DiffSinger
How to get the predicted K_steps? Question about Boundary predict
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Description
Hi,
I am training a singing model following this pipeline with a different dataset.
I wonder how to get the predicted K_steps from trained fs model for ds model, rather than just use K_steps = 60 .
I have tried to find it out but failed. Could anyone give me a hand? Much thanks!
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
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Research direction
Start with the linked docs/README-SVS-opencpop-cascade.md pipeline and trace how the trained fs model relates to the ds model. Investigate how Boundary predict obtains K_steps instead of using the fixed value 60. Done means documenting a supported way to obtain the predicted K_steps, if one exists.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100