yairamr/SE-Probe-data

SE-Probe full results dataset

Pre-computed CKA, diffusion-map, and probing results for SE-Probe, the public code release for "Where Does Speech Enhancement Adapt? Probing Study Under Controlled Degradation" (Amar, Ivry, Cohen, 2026).

📄 Paper: arXiv:2512.00482

Layout

• snr/cka_snr_<model>.parquet: per-architecture (MUSE, MP-SENet, Demucs) CKA values across additive-noise SNRs and DEMAND noise types, with per-row audio quality metrics (PESQ, STOI, SI-SDR, DNSMOS family).
• reverb/cka_reverb_muse_epoch_<N>.parquet: per-epoch reverb-FT MUSE probing parquets. Epoch 48 is the final fine-tuned model; the others trace the fine-tuning trajectory.
• diffusion_maps/: pre-computed diffusion-map embeddings per (model, snr, noise, layer).

Total ~3.1 GB. To download into a local SE-Probe checkout: python scripts/setup.py --full-data.

Citation

@article{amar2026seprobe,
  title         = {Where Does Speech Enhancement Adapt? Probing Study Under Controlled Degradation},
  author        = {Yair Amar and Amir Ivry and Israel Cohen},
  year          = {2026},
  eprint        = {2512.00482},
  archivePrefix = {arXiv},
  primaryClass  = {eess.AS},
  url           = {https://arxiv.org/abs/2512.00482}
}

License

MIT.