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