Voice AI agents are reshaping customer interactions. What separates successful deployments from the rest is choosing the right speech-to-text foundation. The global speech-to-text API market is projected to reach $8.57 billion by 2030, growing at 14.4% annually, yet many teams still struggle with fragmented vendor setups, unpredictable latency, and accuracy issues in production.

If you're evaluating STT for real-time voice AI agents, you need concrete benchmarks for accuracy, latency, and codec performance. This guide walks you through exactly what to test, how to measure results, and where HD codecs make the biggest impact.
Standard telephony uses narrowband audio (8 kHz sampling, ~300–3400 Hz). HD Voice using G.722 or Opus in wideband samples at 16 kHz and extends usable bandwidth to ~7 kHz, which makes high-frequency consonants clearer (for example, ‘fifteen’ vs ‘fifty’).”
Consider this: 73% of organizations cite accuracy as the primary obstacle to voice tech adoption, while 66% struggle with accent and dialect recognition. HD codecs directly address these challenges by capturing the full frequency spectrum of human speech, In practical terms, HD audio delivers:
Start with these baseline tests to measure transcription accuracy:
Numbers and alphanumerics
Similar-sounding words
Background noise conditions
Track word error rate (WER) for each scenario. I. Your production STT should target sub-5% WER for critical use cases like payment processing or medical terminology.
Round-trip latency determines whether your voice AI feels conversational or robotic. Break down your measurements:
Audio capture to transcription
End-to-end conversation flow
Total target: Under 2 seconds for complete turn-taking. When STT, TTS, and telephony infrastructure share the same network backbone, you eliminate 100-300ms of inter-vendor latency.
Run identical test scripts through different codec configurations:
| Codec | Sampling rate | Bitrate | Frequency range | Best for |
|---|---|---|---|---|
| G.711 (narrowband) | 8 kHz | 64 kbps | 300-3400 Hz | Legacy systems, basic telephony |
| G.722 (HD voice) | 16 kHz | 64 kbps | 50-7000 Hz | Business VoIP, clear conversations |
| Opus (modern HD) | 8-48 kHz variable | 6-510 kbps adaptive | Full range with dynamic optimization | Voice AI, music, maximum flexibility |
Document WER differences, particularly for:
"I need to schedule a follow-up for my hypertension medication.
My doctor is James Martinez—that's M-A-R-T-I-N-E-Z.
I'm available Tuesday after 2:30 p.m. or Thursday morning before 11."
Test for: Medical term accuracy, name spelling, time parsing
"My account number is 4-8-2-9-6-7-3-5-1.
I'd like to transfer fifteen hundred dollars, not fifty hundred.
The routing number is 0-2-1-0-0-0-0-2-1."
Test for: Numeric precision, amount disambiguation, security compliance
"The error code is E-X-4-0-9-dash-B-R-K-T.
I've already tried restarting the router and clearing the DNS cache.
My firmware version is 12.3.45 build 2879."
Test for: Alphanumeric accuracy, technical terminology, version number parsing
[Test with various accents]
"I'd like three large lattes with oat milk,
two chocolate croissants. Actually, make that three,
and one gluten-free blueberry muffin."
Test for: Accent handling, quantity changes, dietary terminology
When paired with HD codecs, speech-to-text (STT) delivers real impact: shorter handle times, better first-call resolution, and fewer back-and-forths.When agents and AI assistants hear customers clearly, they resolve issues without repetition.
Real-world impact:
By 2025, AI is expected to handle 95% of customer interactions. That future needs high-fidelity audio to work. HD STT delivers the clarity needed for natural conversation at scale.
Most teams cobble together STT from one vendor, telephony from another, and TTS from a third. This fragmented approach creates three critical problems:
Latency compounds across vendors: Every network hop between services adds extra latency. When your audio travels from a telecom provider to a cloud STT service, then to your application, then to a TTS provider, you're adding 200-400ms before you even start processing. That's the difference between a natural conversation and an awkward pause.
Costs spiral unpredictably: Multiple vendors mean multiple markups, extra fees, and per-minute charges that vary by region. You're paying for the same audio to traverse multiple networks, with each vendor taking their cut.
Compliance becomes a nightmare: Try explaining to auditors why PHI flows through three different companies' infrastructure, each with their own data residency policies and security certifications. One weak link compromises your entire compliance posture.
Telnyx built what others can't: native telecom infrastructure with AI processing on the same network. Here's why that matters:
Colocated GPUs at telecom PoPs While competitors route your audio to generic cloud regions, Telnyx runs STT/TTS processing directly at telecom points of presence. Your audio never leaves our private IP network, cutting latency to sub-200ms for a round-trip time consistently.
True single-vendor simplicity
Regional compliance built in Deploy in the regions you need with automatic data residency. HIPAA, GDPR, and other certifications cover the entire stack, not just pieces of it.
HD STT performance depends on your entire voice stack working together. Begin with these steps:
For Voice API and TeXML:
For AI Agents:
When you're ready to test with infrastructure purpose-built for voice AI, Telnyx offers a fundamentally different approach. As a Tier-1 carrier with colocated AI processing, we deliver what fragmented setups can't: predictable low latency latency, native and free HD codec support from ingress to processing, and compliance that covers your entire voice stack.
Ready to test HD STT on infrastructure that actually delivers? Connect with Telnyx to run your evaluation scripts on our integrated voice platform and see the difference full-stack control makes.
Related articles