RVC-Project / RVC-Project/Retrieval-based-Voice-Conversion-WebUI
[Feature Request] Nvidia Pytorch implementation of BigVGAN for higher quality and speed
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 38.4k
- Forks
- 5.3k
- PR merge metrics
- No merged PRs in 30d
Description
BigVGAN is a Universal Neural Vocoder with Large-Scale Training, it looks very robust even in extreme situations. Nvidia already made a Pytorch implementation of it here : https://github.com/NVIDIA/BigVGAN?tab=readme-ov-file
The audio demos seem to have quite a bump in quality over all other techniques : https://bigvgan-demo.github.io/
Would it be possible to implement it?
Contributor guide
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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.
- Open a pull request that references the issue number.
Research direction
No project files, tests, or entry points are named. Start by comparing NVIDIA's BigVGAN PyTorch implementation with this repository's current voice-conversion and vocoder setup, then define the integration scope and measurable quality and speed checks. Done should include a working implementation with evidence against those checks.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- audio-video-rtc, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100