# WhenToSpeak Controller Notes

The controller is training-free. It consumes signals from a `Brain` interface and
never loads or calls a model itself. The live brain must provide, for each
incremental transcript update and each agent context, mean token surprise, a
last-layer hidden vector, readiness, and turn-end probability.

## Signals

- `surprise`: mean per-token negative log-likelihood of the newly added user
  tokens, teacher-forced.
- `hidden`: mean last-layer hidden-state vector for the newly added tokens.
- `readiness`: speculative reply confidence for this agent. Draft about eight
  tokens and compute `readiness = 1 / (1 + mean_token_entropy)`.
- `p_end`: heuristic probability that the human turn is complete. The live loop
  should combine trailing silence, sentence-final punctuation, and high EOS
  probability.

## Urge

Each agent keeps an online running mean/std of surprise and uses the current
z-score. Hidden-state cosine deltas feed Adams-MacKay BOCPD; a collapse in MAP
run-length becomes the change-point score.

```text
U_t = w_surprise*z(surprise)
    + w_change*changepoint_score
    + w_readiness*readiness
    + w_end*p_end
    + w_barge*max(z(surprise), 0)*readiness*(1 - p_end)
```

`tau` is the single global conversational-aggressiveness knob. Lower `tau` makes
the panel take the floor sooner; higher `tau` makes it wait.

## Arbitration

Each tick is deterministic. Agents first classify local intent as `SILENT`,
`BACKCHANNEL`, `TAKE_FLOOR`, or `INTERRUPT`. Only the highest-urge agent above
`tau` may take the floor or interrupt. Non-winning agents may still backchannel
if their urge clears the derived backchannel threshold. A short refractory period
prevents repeated firing on adjacent ASR updates.