MoonInTheRiver / MoonInTheRiver/DiffSinger
Inference audio generated at higher speed than training files
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 4.9k
- Forks
- 826
- PR merge metrics
- No merged PRs in 30d
Description
Finally, after a lot of labor, I got a decent English singer out of the model, which is great. But the audio generated during inference consistently plays back about 1.3 times faster than the training data fed in. The pitch and the phonemes are correct, but everything's sped up. Any idea why that would be the case? Thank you.
Contributor guide
No contributing guide indexed for this repository
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.
- Open a pull request that references the issue number.
Research direction
No files, tests, or entry points are named. Start by tracing how training audio timing and inference output timing are handled, then compare their sample-rate or duration assumptions. Done means inference audio plays at the same speed as the training files without changing the correct pitch or phonemes.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100