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license: mit
library_name: pytorch
tags:
- speech-editing
- speech-synthesis
- text-to-speech
---
# wavepainter
Released checkpoints for [wavepainter](https://github.com/pujariaditya/wavepainter),
a masked-span speech editor.
On the English `full` split of Ming-Freeform-Audio-Edit, against Ren et al.
([arXiv:2602.00560](https://arxiv.org/abs/2602.00560), the row with GRPO):
| edit type | metric | Ren et al. | wavepainter |
|---|---|---|---|
| substitution | WER | 4.41 | **3.063** |
| insertion | WER | 4.97 | **4.128** |
| deletion | WER | **6.88** | 9.136 |
| substitution | SIM | 0.78 | **0.943** |
| insertion | SIM | 0.82 | **0.961** |
| deletion | SIM | 0.78 | **0.918** |
| substitution | DNSMOS | **3.11** | 2.931 |
| insertion | DNSMOS | **3.18** | 2.905 |
| deletion | DNSMOS | **3.09** | 2.938 |
Five of the nine numbers they report improve on theirs: substitution and
insertion WER, and speaker similarity on all three edit types. We do not beat
them on deletion WER or on DNSMOS anywhere -- see the repository's Limitations.
## Files
- `phase1-base/` — the phase-1 editor. Start here to re-run phase 2 (~1 GPU-hour).
- `phase2-hubert-a085/` — the released model. This produces the numbers above.
## Use
```bash
git clone https://github.com/pujariaditya/wavepainter && cd wavepainter
pip install -e . && ./setup.sh
python scripts/download_weights.py
./scripts/verify_benchmark.sh
```
Checkpoints are sha256-pinned in `scripts/download_weights.py`. Licence and
attribution, including for the components these weights derive from, are in the
repository's `ATTRIBUTION.md`.
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