Find the chapters your listeners won't forgive.
Automated quality checks for AI-narrated audiobooks. Upload your chapters, get a per-file anomaly report in minutes, and regenerate only what's broken.
Why manually checking AI audiobooks breaks down
AI voices are clean at the signal level - no room noise, no clipping. The risks are all at the content level, and they hide in places nobody has time to check.
Voice drift between chapters
Generate 40 chapters across a week and the same voice model can subtly shift - tone, energy, accent. Listeners notice, even if you don't.
Mid-sentence glitches
A half-second artifact, a phantom word, a clipped syllable. Impossible to catch unless you listen to every second with full attention.
Quiet mispronunciations
Names, places, and technical terms the model gets subtly wrong. You catch them on the re-read you don't have time for.
A 10-hour book is 10 hours of listening - and you're doing it twice if you find one bad file.
How it works
From full batch upload to regeneration list in minutes
Upload your chapters as a batch
Drag and drop every chapter file into the dashboard, or POST them to the REST API in a single multipart call. Up to 500 files per batch. MP3, WAV, OGG, FLAC, M4A all supported.
Run the scan
Pick your checks - voice consistency, audio quality, speaking speed, script accuracy - or run all four. The whole batch is analyzed in parallel, usually in minutes.
Regenerate only the flagged chapters
You get a per-file report with scores and flags. Send the flagged chapter list back through your text-to-speech pipeline and re-audit just those for 80% off. The rest of the book is already good to go.
What we catch
Five classes of defect that slip past signal-level checks and only a human would normally notice.
Voice drift between chapters
Every chapter is compared against the rest of the batch. Any chapter whose voice fingerprint drifts gets flagged.
Learn moreMid-sentence artifacts
Glitches, phantom words, clipped syllables, noise bursts, and transient defects that only happen for a fraction of a second.
Learn moreProsody and pacing anomalies
Chapters that drop into robotic pacing, rush through dialogue, or plod through narration - measured in words-per-minute and compared to the rest.
Learn moreSpeaker inconsistency
When the voice starts sounding like a different person halfway through - a fallback from a neural voice, a regional server difference, a model update you weren't told about.
Learn moreOutlier pronunciations and missing words
Script accuracy check transcribes every chapter and compares it against your source text. Repetitions, spoken SSML tags, dropped sentences, and phonetic misses get called out.
Learn moreA real audit, played in your browser
This is a real batch we audited - three tracks from a 13-file tour. Two matched the intended American voice. One came back Scottish, and we don't fully know why. Press play on each file - you'll hear the anomaly our scanner flagged in 30 seconds. A human listening to all 13 files would have taken 15 minutes, and that assumes they stayed sharp through all of them.
An American voice went Scottish on one file
Three consecutive tracks from a 13-file batch. Two matched the baseline. One came back flagged.
| File | Deviation | Status |
|---|---|---|
Beach Ballroom American accent, matches baseline | Pass | |
Linx Ice Arena Unintended Scottish accent | +32.7% | Flagged |
Beach Leisure Centre American accent, matches baseline | Pass |
The same workflow runs on an 80-chapter book. Upload the batch, get back one list of flagged files. Regenerate just those.
Start free
Every new account gets 100 free credits. One credit runs one check on one file, so with all four checks enabled that's enough to audit roughly 25 chapters before you pay a cent. Credits never expire.
Frequently asked questions
Ship an audiobook you trust.
100 free credits on signup. No credit card required.