rtx-csm: perf_history — per-emotion seed × context interaction

Cross-emotion × Carlini context at Amini-best seeds reveals the
"magic combo" doesn't fully transfer:

  happy@42    Amini WER 0.21  →  Carlini WER **0.071** (transfers!)
  angry@100   Amini WER 0.93  →  Carlini WER 1.21 (URL drift)
  fearful@7   Amini WER 0.86  →  Carlini WER 1.00 ("Screw it")
  sad@7       Amini WER 0.93  →  Carlini WER 1.00 (no transcript)

Only happy@42 cleanly generalizes across contexts. The previous
"context-robust" claim was too strong — the (emotion, seed, context)
interaction matters. Cosine vs context stays high for angry (0.95)
even when text drifts, so voice character preservation is the more
robust property than text fidelity.

Honest production interface: `emotional_speech_n.sh` rolling 5 seeds
per (context, prompt). The single-shot recipe lands well only when
all dimensions align, but the picker absorbs the variance.

Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]>

crates/models/rtx-csm/docs/perf_history.md

@@ -338,6 +338,36 @@ character holds when the speaker is consistent in the reference.
 Empirical conclusion: the recipe is **context-robust** on speaker
 identities the picker selects correctly. WER 0.071 on Carlini means
 single-shot near-verbatim emotional speech is achievable.
+
+#### Per-emotion seed × context interaction
+
+Cross-emotion bench at the per-emotion best-seed-for-Amini, run
+against Carlini context:
+
+  emotion  seed  cos_ctx  WER     transcript
+  happy    42    0.958    **0.071** "So today I want to share something
+                                     with you that I have been
+                                     thinking about." ⭐
+  angry    100   0.953    1.21      "...if you have any questions,
+                                     please contact me at
+                                     www.makashvita.com" (URL drift)
+  fearful  7     0.543    1.00      "Screw it" (premature EOT)
+  sad      7     0.399    1.00      (truncated / no usable transcript)
+
+Only `happy@42` cleanly transfers from Amini to Carlini context.
+Angry preserves Carlini's voice character (cos 0.95) but the text
+drifts to URL spam — the model committed to a different content
+direction even with proper steering.
+
+**The "magic combo" of `(emotion, seed)` is context-specific.** The
+per-emotion best seed is found per (context, prompt) pair, not
+globally. The previous claim of cross-context robustness was too
+strong — only happy@42 genuinely generalizes across the two tested
+contexts.
+
+Practical takeaway: `emotional_speech_n.sh` rolling 5 seeds remains
+the right consumer interface. The single-shot recipe lands well only
+when (emotion, seed, context, prompt) all align.
 - *RAVDESS corpus shape biases output length*: clips are ~3 s
   ("Kids are talking by the door") so the steering biases the
   model toward terse outputs (one or two words). Longer-utterance