docs: WO30 — Hebrew learned-IPA v0 (audio-supervised student, run-032) (#287)

Co-authored-by: Ronald Tse <ronald.tse@gmail.com>

Author: ronaldtse

TODO.sota/00-README.md

@@ -65,6 +65,7 @@ hf jobs run --flavor a100-large -d \
 | 25 | 25-ar-news-specialist.md | P1 | 17 | VERDICT: OOD 10.13/8.98 (crown), ID 5.50; export staged |
 | 27 | 27-ar-large-id-arm.md | P1 | — | NEGATIVE — 2.5765 parity with r7; capacity closed on AR too |
 | 28 | 28-oracle-complementarity.md | P2 | — | CLOSED — ceiling 96.78 real; naive voting catastrophic |
+| 30 | 30-heb-learned-ipa-v0.md | P1 | 09 | RUNNING (run-032, FLEURS audio-supervised student) |
 | 26 | 26-heb-noisy-student.md | P1 | 04 | stage 1 RUNNING (labeling); stage 2 staged |
 
 ## Schedule

TODO.sota/30-heb-learned-ipa-v0.md

@@ -0,0 +1,11 @@
+# WO30 — Hebrew learned-IPA v0 (first trained Hebrew G2P we own)
+
+RUNNING (run-032, l4x1): FLEURS he_il (~5K utterances, CC-BY-4.0)
+phoneme-labeled by the universal CTC (the stage-2-GO supervision) →
+byt5-small seq2seq text→IPA student, small-data regime.
+
+- Gate: phonikud heb-g2p-benchmark CER < our rules layer (0.2393).
+- Stretch: Nakdimon-class (0.1102).
+- If v0 clears the gate: scale decision = ivrit.ai (~1,700h at
+  $0.28/audio-hour ≈ $500) for the ReNikud-class run.
+- NO LLM labels anywhere in the chain.