# How to Evaluate STT for Voice Agents in Production

Page: https://stenobird.com/podcast/tech-stories-tech-brief-by-hackernoon-6365648/how-to-evaluate-stt-for-voice-agents-in-production
Text version: https://stenobird.com/podcast/tech-stories-tech-brief-by-hackernoon-6365648/how-to-evaluate-stt-for-voice-agents-in-production.md
Podcast: [Tech Stories Tech Brief By HackerNoon](https://stenobird.com/podcast/tech-stories-tech-brief-by-hackernoon-6365648)
Published: 2026-05-02T16:00:42+00:00
Episode link: https://share.transistor.fm/s/01d3aa84
Audio file: https://media.transistor.fm/01d3aa84/5ef5b47c.mp3
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JSON: https://stenobird.com/v1/public/podcasts/tech-stories-tech-brief-by-hackernoon-6365648/episodes/how-to-evaluate-stt-for-voice-agents-in-production
Duration seconds: 837

## Resource

This story was originally published on HackerNoon at: https://hackernoon.com/how-to-evaluate-stt-for-voice-agents-in-production . Most STT benchmarks measure the wrong thing. Here's how to evaluate speech-to-text for voice agents using the metrics that actually drive production performance Check more stories related to tech-stories at: https://hackernoon.com/c/tech-stories . You can also check exclusive content about #ai-voice-agent , #voice-agent-stt , #pipecat , #voice-ai , #conversational-ai , #ai-voice-agent-benchmarking , #stt-evaluation-metrics , #good-company , and more. This story was written by: @speechmatics . Learn more about this writer by checking @speechmatics's about page, and for more stories, please visit hackernoon.com . Voice agent developers are optimising for TTFB — time to first byte — but it's one of the least useful metrics in production. What actually determines how fast and reliable your agent feels is TTFS (time to final segment): the gap between a user finishing speech and a stable transcript landing in your LLM. This piece breaks down the Pipecat benchmark — currently the most credible public eval for STT in voice agents — explains semantic WER and why it beats standard word error rate for this use case, and makes the case that accuracy and latency are inseparable. A faster wrong answer is still a wrong answer.

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