# VoiceAcousticTransfer — P2a noise_flow (2026-07-09)

- `p2a_noise_flow_scaled_lufs20_40k_best_step40000.pt` — recording-condition transfer model
  (conditional flow matching, hidden 1024 / depth 16 / heads 16, 40k steps, LUFS-normalized
  raw-DAC caches). Optimizer stripped; contains model + EMA + all metadata incl.
  `latent_scale` (1.652), `daps_to_idx`, `style_to_idx`.
  Inference: Euler t 0->1, 32 steps, joint-axis CFG 2.0; inputs loudness-normalized to -20 LUFS.
- `trackb_condition_analyzer_best.pt` — standalone recording-condition analyzer
  (contrastive encoder + a18/recipe-parameter regression + DAPS classifier heads).
- `condition_gmm.joblib` — in-the-wild condition prior (GMM over analyzer embeddings).

Code, evaluation harness, and usage: https://github.com/Kiberchaika/VoiceAcousticTransfer
(branch `rec-con-diffusion`); run log `8jul_acoustictransfer_evolution_report_journal.md`.