What matters when building an AI voice app
Notes from building voice practice flows: recording quality, transcription, scoring, latency and feedback that users can act on.
Voice AI apps look impressive in demos, but they are easy to make annoying in real usage.
The user is speaking out loud. That already takes effort. If the app records badly, transcribes poorly, waits too long or gives vague feedback, the user will not trust it.
Recording is part of the UX
The recording screen should feel calm. The user needs to know:
- when recording starts
- how long they have been speaking
- whether audio is being captured
- what happens after they stop
I prefer a simple state machine for this.
type RecordingState =
| "idle"
| "recording"
| "uploading"
| "transcribing"
| "analyzing"
| "complete"
| "failed";That gives the UI clean states instead of one vague loading spinner.
Transcription is not the final product
Transcription is only the first layer. The user does not open a speaking app just to see their words. They want to know how to improve.
A useful feedback result should be specific:
- what was clear
- what sounded weak
- which filler words appeared
- whether the answer was too long
- how to say it better
“Good answer, be more confident” is not enough. The app should show a stronger version of the answer and explain why it is stronger.
Scoring needs to be explainable
Scores are useful only if they map to something the user understands. In SpeakSure, I think about scores as categories, not decoration:
- clarity
- confidence
- conciseness
- pacing
- filler control
A score should never be the whole feedback. It should be a quick summary that points to the detailed explanation.
Latency changes the product
Voice flows are sensitive to waiting time. If the analysis takes too long, users start doubting whether the app worked.
A better approach is to show progress in stages:
- uploading audio
- transcribing answer
- analyzing structure
- building feedback
This does not make the backend faster, but it makes the wait feel understandable.
The best feedback is reusable
The real value of a voice app is not one analysis. It is history. If the app can show recurring patterns, repeated filler words and improvements over time, the product becomes more useful than a single AI response.
That is the difference between a voice demo and a product people can train with.