Dictation App Reviews: What Users Say About Each App

Calculated from the rows

Every statistic is calculated by code from the rows above. Open one to see the exact values it summarises.

• 555 data pointsThe what App Store reviewers praise and complain about, app by app: coded reviews of dictation and transcription apps dataset holds 555 data points, each a published figure traced to its source.Calculated from other facts

How this dataset is built

What counts as a row

Every app in our market registry with at least 30 of its App Store reviews about dictation or speech to text coded: the reviews shown on its public App Store pages in seven English-speaking storefronts (US, UK, Canada, Australia, India, Ireland, New Zealand), each coded as a whole against the same codebook as the study of all reviews.

What does not

Apps with fewer than 30 coded reviews about dictation, reviews about something else (set aside), Hacker News comments and Bluesky posts (a comment found by an app's name often weighs several apps), themes no review of the app states, and our own app.

How rows are found and checked

Reviews are gathered by code from each app's public App Store pages, then each one is coded as a whole by a researcher against the published codebook (themes, and whether each is reported as a problem, praised or only mentioned) before anything is counted; a second researcher codes a fixed 10% sample of all documents independently and the agreement per theme is published with the study. For each app and theme, the share of its coded reviews that report a problem with it or praise it is calculated by code, with the count, the number of reviews and the 95% Wilson score interval.

What the data cannot tell you

Apple shows a selection of reviews on an app's page (often long and helpful ones), not a random sample, and unhappy reviewers write more. With 30 to 63 reviews per app the 95% intervals are wide, often 15 to 25 points: a difference between two apps means little unless their intervals do not overlap. Reviews can be years old and describe an earlier version of the app. The coding is done by a language model following written rules, so single reviews can be miscoded.

The whole method, from search to calculation, is on the research data page.

Cite and reuse

You may copy, share and adapt this dataset for any purpose, including commercially, if you credit it with a link. Quoted passages remain their authors' words: cite the original source for those.

Yap (2026). What App Store reviewers praise and complain about, app by app: coded reviews of dictation and transcription apps [Data set]. https://yapapp.cc/data/app-review-themes

License: CC BY 4.0.

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