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open-standards/aac/conformance/v1/adaptive.json
Transaction Science edcf02b350 feat(access-core, aac-core): Bayesian selection that never moves a cell, and prediction in 43 languages 
Selection (access-core; SPEC §5.4, proposed): a prior over the options on the
board — usage frequency now, the Laya decision model later — times the
person's own switch-timing likelihood, after Nomon (Broderick & MacKay):
- press_timing.rs learns a damped kernel-density estimate of each press's
  offset from the intended highlight, from a population prior scaled to the
  person's scan interval, and only from selections the person keeps: presses
  are staged per attempt, dropped when abandoned or undone (including an Undo
  reached by scanning), and learned only after three newer selections.
- selection.rs computes the posterior (late presses explained as late, a
  2% lapse term), selects at 99:1 odds with the prior capped so presses must
  favour the choice 4:1, and otherwise keeps scanning — a row gets up to two
  extra passes. Without opt-in, or before 10 kept presses, it behaves exactly
  like the conventional scanner and only measures.
- scan_order.rs orders rows, groups and cells by prior mass (fewest expected
  steps) without moving any; options keep stable position-order ids, and a
  new order applies from the next pass. dwell.rs weights per-cell dwell from
  0.8x to 1.5x within hard bounds. Every adaptation is opt-in and previewable.
Conformance C8–C11 (order never moves a position, opt-in required, dwell
bounds, selection follows presses): 370/370 with the original 236.

Prediction (aac-core): per-language packs — word frequencies, word pairs,
sentence starts and a letter model, front-coded and CRC-checked — built
reproducibly by tools/lang/build_packs.py from pinned wordfreq 3.2.0
(CC-BY-SA-4.0), FrequencyWords 2018 (CC-BY-SA-4.0) and Common Voice sentences
(CC0), into data/lang/ (43 of 45 languages; gu and kn have no open source
large enough and report "adaptive only"). PredictionEngine blends a pack with
what the person has said (hierarchical Dirichlet smoothing): next word,
completion, and letter prediction for letter scanning, deterministically.
A per-language pair filter exists; its lists still need curating before the
app shows next-word suggestions to children.

Co-Authored-By: Claude Opus 5.5 <[email protected]>
2026-09-29 11:28:26 -04:00

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"dwell": {
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"bounds": "lo = max(ceil(0.8 D), min(D, 300)) (>= 150 for any D >= 150); hi = max(min(floor(1.5 D), max_dwell_ms), D, lo)",
"dwell": "clamp(round(D * factor), lo, hi)",
"factor": "x = ln(n p / sum p): x >= 0 -> 1 - 0.2 tanh(x / ln 4); x < 0 -> 1 + 0.5 tanh(-x / ln 4); p = 0 -> 1.5; all zero -> 1",
"max_factor": 1.5,
"min_factor": 0.8,
"person_dwell": "applying weights never changes D, never proposes, and never resets the section 5.3 measurement window; weights applied during a dwell take effect when it ends; opting out restores D at once and forgets the weights",
"proposal_floor_ms": 300
},
"dwell_weighting_default": false,
"order": "units (rows | cells | groups | blocks) by descending sum of weights, members by descending weight; ties by position (row-major); unit membership is the fixed scan's",
"selection": {
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"decision": "select the leader when ln-odds over the runner-up >= ln win_odds; a lone option when sum ln L - n ln(lapse / S) >= ln(win_odds / prior_odds_cap); else keep scanning; ties to the lower index; not opted in or fewer than min_confirmed kept presses: the latest highlight at or before the last press",
"density": "f(x) = [w0 N(x; 0.65 T, max(0.25 * 0.65 T, 10)) + sum_i d^i N(x; y_i, h)] / (w0 + sum_i d^i); y_0 newest; w0 = 25 d^n; h = max(10, 1.06 sd n_w^-0.2) with sd, n_w the weighted spread and total weight of prior and samples",
"history": 95,
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"kernel_evaluations": "presses x onsets in the window x (kept samples + 1)",
"lapse": 0.02,
"learning": "presses are staged per selection across its levels; a top-level choice discards what was staged before it; on the final cell the staged presses become a pending selection; an Undo reached by scanning discards itself and the selection it undid; a selection is learned once undo_depth + 1 newer selections are completed; of a Bayesian selection only presses with (1 - lapse) f(offset) > lapse / S are learned",
"likelihood": "L_j(t) = (1 - lapse) max_c f(t - onset_{j,c}) + lapse / S over onsets with -T/2 <= t - onset < 2T (none: f = 0); S = last onset - first onset + T",
"min_bandwidth_ms": 10.0,
"min_confirmed": 10,
"offset_window_intervals": [
-0.5,
2.0
],
"options": "an option is its position-order index at its level, never its rank in a pass",
"population_mean_fraction_of_interval": 0.65,
"population_sd_fraction_of_mean": 0.25,
"prior": "normalise; floor each at max / prior_odds_cap; renormalise",
"prior_odds_cap": 24.75,
"prior_weight": 25.0,
"rule_in_force": "a rule with win_odds / prior_odds_cap < 4 (or non-finite, win_odds <= 1, prior_odds_cap < 1) is replaced by the default",
"undo_depth": 2,
"win_odds": 99.0
}
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"option": 1
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0.0041975520854075285,
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1040.0,
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1080.0,
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1070.0,
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"expected_posterior": null,
"interval_ms": 1000,
"learned_offsets_ms": [
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1060.0,
1020.0,
1080.0,
1050.0,
1030.0,
1070.0,
1045.0,
1055.0,
1065.0,
1035.0,
1050.0
],
"name": "a press before any highlight selects nothing",
"onsets": [
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0,
0.0
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[
1,
1000.0
],
[
2,
2000.0
],
[
3,
3000.0
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[
4,
4000.0
]
],
"opted_in": false,
"presses_ms": [
-50.0
],
"priors": [
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0.2,
0.2,
0.2,
0.2
]
},
{
"expected_decision": {
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},
"expected_kernel_evaluations": 13,
"expected_posterior": [
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],
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1060.0,
1020.0,
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1050.0,
1030.0,
1070.0,
1045.0,
1055.0,
1065.0,
1035.0,
1050.0
],
"name": "an onset more than two intervals away explains nothing",
"onsets": [
[
0,
0.0
],
[
1,
1000.0
]
],
"opted_in": true,
"presses_ms": [
2600.0
],
"priors": [
0.5,
0.5
]
},
{
"expected_decision": {
"kind": "select",
"method": "bayesian",
"option": 0
},
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"expected_posterior": [
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1055.0,
1065.0,
1035.0,
1050.0
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"name": "a lone option selects on a press it explains",
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0,
0.0
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1050.0
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1.0
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},
{
"expected_decision": {
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"expected_posterior": [
1.0
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1050.0,
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1070.0,
1045.0,
1055.0,
1065.0,
1035.0,
1050.0
],
"name": "a lone option does not select on a press it cannot explain",
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0,
0.0
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"presses_ms": [
5000.0
],
"priors": [
1.0
]
}
],
"spec": "SPEC.md §3, §5.1, §5.4 (proposed, after 0.2.0)",
"standard": "aac",
"vector": "adaptive",
"version": "0.3.0-draft"
}
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