Autocorrect

CleverKeys autocorrect knows that adjacent keys are more likely typos than distant ones. When you type tge instead of the, it weights g→h as a much cheaper substitution than g→x because g and h are physically neighbors on QWERTY. This page walks through the full pipeline, the settings you can tune, and how contractions and accents interact with it.

Quick Summary

What	Description
Purpose	Fix tap-typing mistakes using keyboard physics + dictionary frequency
Access	Automatic while typing; toggle in Settings → Word Prediction
Undo	Tap the original word in the prediction bar
Layouts	Adapts automatically to AZERTY / QWERTZ / Dvorak / custom layouts
Languages	Latin accents (é, ñ, ü, etc.) covered out of the box

How Autocorrect Works

When you finish a word (by pressing space or punctuation):

1. Exact alias check — if the typed word is a known contraction base (dont, im, cant), it expands directly (don't, I'm, can't).
2. Dictionary hit — if the word is in the dictionary as-is, no correction.
3. Length / prefix gates — words shorter than the minimum length, or that violate the prefix rule, are skipped.
4. Adjacency-weighted dictionary scan — every dictionary word within max_length_diff characters is scored by keyboard physics:
   • Same length: each position contributes a substitution score from 1.0 (exact match) down to ~0 (max-distant keys). Adjacent keys score ~0.89.
   • Different length: weighted Levenshtein distance where insert/delete cost 1.0 but substitution cost is the normalized key distance.
5. Four-tier tiebreaker — picks the winner using score, frequency, and alias preference. Details below.
6. Alias rerouting — if the winning candidate is a contraction base (dont → don't), the apostrophe form is returned.
7. Capitalization preservation — Teh → The, TEH → THE.

The Key Proximity System

Each letter has an (x, y) position on the keyboard grid. Substitution cost between two letters is the normalized euclidean distance between their key centers:

Pair	Why	Score
e ↔ e	Same key	1.00
g ↔ h	Adjacent home row	~0.89
t ↔ y	Adjacent top row	~0.89
q ↔ s	Diagonal one key away	~0.80
q ↔ p	Opposite ends of top row	0.00

So tge → the (one g↔h substitution, score ~0.96) ranks far above tge → tax (which would require two distant substitutions). The result: closer to your actual fingertip travel, less random-looking corrections.

Layout-Aware Adjacency

Adjacency is computed from your actual keyboard layout, not a hardcoded QWERTY map. When you switch to AZERTY (where a and q swap from QWERTY positions), or use Dvorak, or load a custom layout, the proximity model updates automatically. French AZERTY users get the right adjacency for their q↔a typos; QWERTZ users get y↔z treated as adjacent.

Accented Letters

Common Latin diacritics (é, ñ, ü, ç, ß, å, ø, ý and ~20 others) share the position of their unaccented base. So:

• cafe → café — distance is 0 on the accent position. Correction is free.
• senor → señor — same.
• mude → müde (German) — same.

If you’re on a keyboard layout that has a dedicated accent key, the real key position overrides this default. The accent fallback only kicks in when the keyboard doesn’t have a physical key for the accented form.

Contractions

If you type a contraction base — dont, cant, im, hadnt, couldnt, youre — it expands to the apostrophe form (don't, can't, I'm, hadn't, couldn't, you're). The full list lives in dictionaries/contractions_en.json.

If you mistype a contraction base — donr, hadnr, couldnr — the adjacency-weighted scan picks the closest contraction and reroutes to the apostrophe form. So donr → don't, hadnr → hadn't, couldnr → couldn't. The selection logic prefers structural closeness (a single adjacent-key sub) over dictionary popularity here — hadnr becomes hadn't not hasn't because the d-to-t alignment requires fewer substitutions.

Words that are valid English even though they look like contraction bases (well, were, hell, shed, shell, wed) are protected from this expansion — well stays well, not we'll.

Undoing Autocorrect

If autocorrect changes a word you didn’t want changed:

Method 1: Tap the Original Word

1. Look at the prediction bar immediately after correction.
2. Your original word appears as a suggestion.
3. Tap it to restore the original spelling.
4. The word is automatically added to your dictionary so it won’t be corrected again.

Method 2: Backspace and Retype

1. Press backspace to delete the corrected word.
2. Retype your intended word.
3. Add it to your dictionary via the prompt that appears.

Adding Words to the Dictionary

When you type an unknown word and autocorrect doesn’t fire:

1. Type the word and press space.
2. A prompt appears in the suggestion bar: “Add ‘word’ to dictionary?”
3. Tap to add. The word will be suggested in future and protected from autocorrect.

[!TIP] Added words appear in your predictions when you start typing them.

Managing Your Dictionary

Open Settings (gear icon on keyboard), then Activities → Dictionary Manager:

Tab	Contents
Active	Words from the bundled / language-pack dictionary
Disabled	Words you’ve turned off — never auto-suggested or autocorrected
User	Words from Android’s system user dictionary
Custom	Words you’ve added yourself

Autocorrect Settings

All in Settings → Word Prediction. Most users only ever touch the top three.

Primary Knobs

Setting	Default	What it does
Autocorrect (autocorrect_enabled)	on	Master toggle
Min word length (autocorrect_min_word_length)	2	Skip autocorrect on very short words
Required prefix length (autocorrect_prefix_length)	0	Candidate must share this many starting chars with your typed word. 0 = no prefix required (lets first-character typos like wuestion → question correct). 2 is the legacy stricter mode.

Advanced Tuning

Setting	Default	What it does
Score threshold (autocorrect_char_match_threshold)	0.65	Minimum match score (0.0–1.0) a candidate must reach. Higher = more conservative.
Max length difference (autocorrect_max_length_diff)	2	Allow candidates whose length differs by up to this many characters. Handles insertion/deletion typos like questin → question.
Min frequency floor (autocorrect_confidence_min_frequency)	100	The winning candidate must have at least this dictionary frequency to actually replace your word. Filters out very rare words.

Swipe Typing

Setting	Default	What it does
Beam autocorrect (swipe_beam_autocorrect_enabled)	on	Apply correction during swipe beam search
Final autocorrect (swipe_final_autocorrect_enabled)	on	Apply correction on swipe completion
Neural frequency weight (neural_frequency_weight)	0.57	How much to weight dictionary frequency vs. neural model confidence in swipe predictions. Higher = trust frequency more.

[!NOTE] neural_frequency_weight lives in the Neural Settings activity (Settings → Neural prediction). It controls the swipe pipeline; autocorrect’s tap-typing path uses the absolute frequency directly via autocorrect_confidence_min_frequency.

Tips and Tricks

• Proper nouns: Add names and places to prevent miscorrection. They’ll then short-circuit the dictionary scan and never get autocorrected.
• Technical jargon: Same as proper nouns — add to dictionary.
• Disabled list: Move a word to the Disabled tab in Dictionary Manager to prevent autocorrect from EVER picking it as a candidate.
• Language-specific behavior: Each language has its own dictionary AND its own contractions file. The adjacency model uses your current keyboard layout, regardless of language.

Common Questions

Q: Why did tge correct to the but tgw didn’t correct to anything?

A: g↔h is one adjacent-key substitution (score ~0.96) for tge → the. tgw would need a substitution for g↔h AND a substitution for w↔e, dropping the score below the threshold.

Q: My word is technical jargon and keeps getting corrected. What do I do?

A: Add it to your dictionary via the “Add to dictionary?” prompt, or via Settings → Dictionary Manager → Custom tab. Once added, autocorrect skips it.

Q: Does autocorrect work for languages other than English?

A: Yes — the adjacency model is language-independent (it’s about which keys you tapped). Each language has its own word dictionary and contractions file.

Q: Why does well stay as well instead of becoming we'll?

A: well is a real English word, so it’s on the protected list. CleverKeys won’t expand it to we'll because that would be wrong in most contexts (“the well ran dry”).

Q: How does autocorrect interact with swipe typing?

A: They’re separate paths. Swipe typing produces candidates via the neural model + beam search, then optionally applies autocorrect on the top candidate (swipe_beam_autocorrect_enabled, swipe_final_autocorrect_enabled). Tap typing uses the dictionary scan described above.

Related Features

• Swipe Typing - Neural word prediction for gesture input
• User Dictionary - Add custom words
• Special Characters - Symbols and accents

Technical Details

See Autocorrect Technical Specification for the pipeline internals, weight calibration, and the four-tier selection logic.