How to Test a Local AI Dictation Browser Extension

Short answer

Test dictation on passages with known wording, inspect extension access, and measure time to an approved draft. Local speech recognition can reduce one data transfer, but the website receiving the text may still save it remotely. Do not equate “local model” with a wholly local workflow.

This is a proposed acceptance method, not a benchmark or a security audit. The Yap Voice Typing review applies the same questions to a submitted browser extension.

1. Separate the data paths

Write down microphone capture, recognition, text insertion and destination storage as four steps. For each, record the component and any external service involved. Ask what happens to diagnostics too. A browser extension and a cloud document editor can have different handling policies even when used in one sentence.

Inspect the store publisher and current permission request. Chrome's permission documentation distinguishes API access, host access and optional permissions. A permission describes capability; it is not proof of what the software actually does. Do not treat the absence of one warning as a complete privacy assessment.

2. Freeze ten test passages

Write five ordinary passages and five difficult ones before starting. Use fictional details. Include a date, an acronym, a foreign name, an amount and a negative instruction. Save the expected wording so you do not unconsciously accept a plausible substitution after hearing yourself dictate.

Use the same room, microphone and browser for the first comparison. Record the model or extension version if visible. Test the candidate against normal typing and any existing dictation tool you already use.

3. Check the entire editing cycle

Measure from activation to approved text. Include startup, dictation, corrections and final reading. Keep consequential meaning errors separate from punctuation. A fast transcript can take longer to repair than a slower but accurate draft.

Repeat failed passages once to see whether the problem is stable. Record both attempts rather than keeping only the better result. Check two editors you actually use, because insertion that works in a plain field may fail in a rich-text document.

4. Test offline behavior narrowly

Complete any required model download first. In a safe test environment, disconnect and repeat a short passage on a surface that remains available. Note what still works and what requires a connection. Passing this test demonstrates that particular behavior; it does not prove every component never transmits data when online.

5. Decide using a written gate

A reasonable starting gate is zero uncorrected consequential errors in the accepted test drafts, reliable cancellation and a manageable correction burden. Set your own time threshold before running the trial. Use nonsensitive drafts until the required data-handling review is complete.

Retest after material changes to permissions, model, browser or target editor. Keep typed input available as a fallback. Read reducing sensitive workflow logs for a related boundary: a useful output can still end up in an unintended record.