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README.md

@@ -19,3 +19,20 @@ montrose, boolooroo). Full breakdown in `worst100_oov_analysis.json`.
 This measurement is the primary justification for the 100-hour training phase: a coverage
 problem calls for coverage. See `Diffusion-ASR/pipeline-code-and-docs` for the full recipe
 and evidence record.
+
+
+## How to read this dataset (verified 2026-08-11)
+
+- **Ranking basis:** clips are ranked by **absolute word-error count** on
+  **Whisper-normalized** text — not by WER percentage. A long clip with 20 errors at 23%
+  WER outranks a short clip at 60%.
+- **Tie band:** the rank-100 cutoff is 4 errors, and 66 clips tie at exactly 4 — which of
+  them appear here is arbitrary among equals.
+- **`substitution_pairs` are raw alignment output**, not claimed confusions: across a
+  garbled stretch, positional pairing produces items like `have→all` that carry no
+  meaning individually. Use `error_classes` for interpretation.
+- Some references contain **genuine dialect spellings** (e.g. `allers`) — that is the
+  LibriSpeech ground truth, not a transcription error.
+- Integrity verification: all 100 references byte-match the official test-clean
+  transcripts; all 100 hypotheses byte-match the model's recorded decode outputs; stored
+  error counts reproduce exactly under the stated normalization.