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Last verifiedOct 19, 2026

AI Scoring Accuracy: Method, Calibration and Limits

Our AI gives a practice estimate as a range, such as 8–9 on the CELPIP scale, never a single score, and quotes the exact words behind it. We have not published accuracy figures yet. After our first calibration round with trained raters, we will report sample size, average error and ±1-level agreement here.

Published results

Accuracy figures

Not yet published

We'll publish these after our first calibration round with trained raters. Until then, no accuracy figure appears anywhere on this site.

Each figure will also be broken down by task, recording source and first-language background.

Sample size
Not yet publishedanswers scored by trained raters
Mean absolute error
Not yet publishedaverage gap, in CELPIP levels
Within ±1 level
Not yet publishedshare of answers within one level
Repeat spread
Not yet publishedsame answer, scored twice
Last calibrated
Not yet publishedand the model version used
Publishing after our first calibration round

Can I trust an AI CELPIP score?

Use it as a study signal, not a prediction. An AI estimate is most useful for spotting your weakest criterion and checking whether a change helps. It can be off by a level, especially on pronunciation and on short answers, so we always show a range, the evidence and our confidence — and never call it official.

Ways to get the most from it:

  • Compare several answers, not one. A pattern across three attempts says more than any single estimate.
  • Watch the criterion that comes out lowest each time — that is where practice pays off.
  • Read the quoted evidence. If a quote does not match what you meant, give that estimate less weight.
  • Before booking the test, combine AI estimates with full timed practice, including the official CELPIP practice tests.

How does AI estimate a level from a recording?

We transcribe your recording with word-level timings, measure pace, pauses, fillers and time used in code, then ask a language model to rate the four CELPIP criteria from the audio, the transcript and those measurements. Every quote it cites is checked against your own words, and the recording is deleted after scoring.

  1. Transcribe with timings

    Speech-to-text keeps fillers such as “um” and gives every word a start and end time.

  2. Measure delivery in code

    Words per minute, pauses of 0.6 s or more, long pauses of 1.5 s or more, fillers per minute and the share of the response time you used are calculated — not guessed by the model.

  3. Rate four criteria as a range

    The model rates content and coherence, vocabulary, listenability and task fulfillment on the 3–12 scale, as a range one or two levels wide, against a checklist for the task. Writing is rated on readability instead of listenability.

  4. Check every quote

    Each piece of evidence must appear word for word in your answer. Anything that does not is removed before you see the report.

  5. Apply fixed rules

    Answers that use less than 40% of the time or have fewer than 50 words are capped at level 6. If the audio itself could not be analysed, the report says pronunciation was judged from the text only.

  6. Discard the recording

    Audio is processed in memory and never stored. Only the transcript and the report are kept — visible to you alone, until you delete them.

What does each criterion look at?

The four criteria and what the estimate is based on
CriterionWhat we look atBased on
Content & coherenceIdeas, how they are organised and connected, supporting detailTranscript or essay
VocabularyRange, precision and natural word choiceTranscript or essay
Listenability (speaking)Rhythm, pausing, fillers, pronunciation, intonation, grammar controlAudio and measured delivery
Readability (writing)Grammar and sentence control, spelling, punctuationEssay
Task fulfillmentEvery part of the task, tone for the listener or reader, use of the time or word rangeTask checklist and timing
The four criteria and what the estimate is based on · CELPIP — test format and scoring (2026-10-18)

How will we calibrate it?

Calibration means comparing our estimates with levels that trained human raters give the same answers.

  • Answers: practice recordings and essays from volunteers who opt in separately — covering all eight speaking tasks and both writing tasks, recorder and uploaded audio, and a range of first-language backgrounds.
  • Raters: teachers with CELPIP or TESL teaching experience score each answer independently, without seeing our estimate.
  • Fixed settings: the model, prompt version and settings are frozen before the comparison, so the figures describe the scoring you actually get.
  • Consent: answers are used for calibration only with separate, opt-in consent, which can be withdrawn at any time.

What will we publish?

Figures we will publish after each calibration round
FigureWhat it tells you
Sample sizeHow many answers were compared, by task, recording source and first-language background
Mean absolute errorThe average gap between our estimate and the raters, in CELPIP levels
Within ±1 levelThe share of answers where our estimate was within one level of the raters
Repeat spreadHow much the estimate for the same answer moves when it is scored again
Date and versionWhich version of the scoring the figures apply to
Figures we will publish after each calibration round

Status: data collection in progress

No accuracy figures are published yet, and none will appear anywhere on this site until they exist. The first round is planned for December 2026; this page will be updated with the results and the date.

What can’t AI judge well?

  • Pronunciation in detail. It hears overall clarity, rhythm and intonation, not individual sounds the way a dedicated pronunciation engine would.
  • Every accent equally. Speech-to-text makes more mistakes with some accents, which can pull an estimate down. That is why we will report results by first-language background.
  • What a transcript hides. Automatic transcripts can smooth over errors or add punctuation you did not speak.
  • Very short or off-topic answers. These get low confidence and capped levels.
  • Memorised templates. We flag answers that sound rehearsed and generic, but this detection is approximate.
  • Your official result. Real CELPIP raters, test-day conditions and the full four-skill test all differ from one practice answer.

Changelog

Changes to how AI scoring works
DateChange
2026-10-19Method published. Scoring versions spk-v1 and wrt-v1: transcription with word timings, four-criterion ranges, verbatim evidence check. No accuracy figures yet.
Changes to how AI scoring works

Questions people ask

Why a range instead of one number?
Because a single practice answer cannot pin a level down. A range such as 8–9 is more honest, and it shows where to aim next.
Is my answer used to train the AI?
No. Recordings are not stored, and transcripts and essays are not used to train models. Calibration uses only answers from people who opt in separately.
Why can two attempts at a similar answer score differently?
Small changes in delivery, transcription or wording can move an estimate. Scoring settings are fixed to keep results repeatable, and we will publish how much repeat scores move.
What if an estimate looks wrong?
Email hello@canadianenglishtest.org with the date and task. Estimates that look wrong help us find problems, and we log every change to the scoring on this page.

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Unofficial practice and estimates — not affiliated with Paragon or IRCC, and not legal advice. Read the disclaimer