Verify naturalness before users hear it
Podonos rates synthetic speech with a calibrated listener model, helping TTS teams avoid slow panels and ship with confidence.
Studies take weeks and thousands. Iteration should not.
TTS teams release 30 or more model variants weekly, while human studies happen once a quarter. That lag lets poor voices ship. Podonos fills it: send audio, receive scores in seconds, and iterate the same day.
Send. Score. Repeat.
Send audio
POST TTS output to the Podonos API, any format or model
Evaluate in parallel
A listener model scores prosody, naturalness, and pronunciation simultaneously
Get results
Receive a MOS-equivalent score, confidence interval, and dimension breakdown in under 3 seconds
Aligned with listener data
Compare popular TTS models
Podonos publishes a monthly benchmark of open-source and commercial TTS outputs, scored through Podonos.
Pricing based on usage
Used by voice product teams
We repeated human evaluations every two weeks to choose between checkpoint candidates. Podonos reduced that cycle to a daily automated check. Now we detect degradation on the day it is introduced.
The MOS correlation with our panel data was sufficient for use as a CI gate. That was the test that convinced us. It does not replace human evaluation, but it provides a reliable early warning.