Audio Quality

Find noise, glitches, silence gaps, and clipping in your TTS output - before your users do.

The problem

TTS output isn't always clean. Providers can produce files with audio glitches, unexpected silence, or clipping - and it often happens randomly across a batch.

Quality regression

A provider updates their model and the overall quality drops. Files that used to sound clear now have a muffled or distant quality. Since there's no error, you only notice when someone complains.

Glitches and artifacts

Clicks, pops, garbled speech, static noise, and digital artifacts appear randomly in TTS output. They're easy to miss in a large batch but immediately noticeable when someone is listening to your content.

Silence gaps

Some providers occasionally return files with long stretches of silence in the middle - or skip entire paragraphs. The API returns success, but chunks of the audio are just empty.

Wasted credits

Every bad file costs you a generation credit. Without automated checking, you're paying for files you'll have to regenerate anyway - and you don't know which ones until someone listens to them all.

What people are saying

"I've been paying for a creator account the last two months, and while I do manage to get satisfying results, it seems to require an ever increasing amount of re-rolls to get acceptable quality."

- u/Mikkel9M on r/ElevenLabs

"Audio quality sounds like I'm standing far away from the mic or something. It was so amazing at first."

- u/Impressive-Kale-20 on r/ElevenLabs

"Total requested audio was 4:31, but from 1:21-2:26 and 3:02-3:36 there was only silence. Also huge volume level changes and style shifts. In short: unusable."

- u/janne.kauttonen on OpenAI Forum

"Some of my texts get synthesized no problem into one neat file. Yet other books encounter problems. I get a bunch of 5-minute chunks and there seem to be a random amount of chunks missing."

- Google Cloud Community

How we detect it

Every file goes through a series of checks designed to catch the issues that TTS providers don't warn you about.

1

We measure the signal-to-noise ratio

Each file is analyzed to separate the voice from any background noise. Files with unusually low clarity get flagged - even if the noise is subtle enough to slip past a quick listen.

2

We scan for glitches and artifacts

We look for clicks, pops, garbled speech, static noise, and digital artifacts that TTS engines sometimes produce. Each artifact is timestamped so you know exactly where the problem is.

3

We check for silence gaps

Files are scanned for unexpected stretches of silence - a common issue where the TTS engine skips phrases or entire paragraphs without returning an error.

4

We detect clipping and bandwidth issues

We check whether the audio is clipping (distorted peaks) or has been downsampled, which can make output sound thin or compressed compared to the rest of the batch.

What you get

A detailed quality report for every file in your batch

star

Quality score

An overall quality rating for each file on a 0-100 scale.

checklist

Artifact log

Every glitch timestamped with type and severity.

volume_off

Silence report

Any unexpected silence gaps with their position and duration.

warning

Clipping flags

Files where audio peaks are distorted or bandwidth is limited.

1 credit per file

Stop shipping broken audio

100 free credits on signup. No credit card required.