Building a voice agent that works across languages forces a hard question early: which text-to-speech engine do you build on? The demos all sound great. Production is where they separate — under real load, across accents, at a cost you can sustain. Here is what we learned comparing the field.
What we were actually optimising for
- Voice quality — natural prosody that holds up across languages, not just English.
- Latency under load — time-to-first-audio when many calls hit at once, not in a quiet benchmark.
- Cost at scale — per-minute economics that survive real call volume.
- Multilingual coverage — the specific languages and accents our users actually speak.
The trade-off map
| Priority | What gives | What to watch |
|---|---|---|
| Best voice quality | Often higher latency / cost | Streaming and caching to hide it |
| Lowest latency | Sometimes thinner voices | Quality floor on key languages |
| Lowest cost | Coverage and naturalness vary | Test your languages, not the demo’s |
The lessons
- Benchmark under concurrency — idle latency tells you nothing about a busy line.
- Stream audio so perceived latency stays low even when generation isn’t instant.
- Test on your real languages and accents; aggregate scores hide the gaps that matter.
“A TTS engine that sounds perfect in a demo can fall apart on a busy multilingual line. Choose for the load you’ll actually carry.”
KnackLabs
