By Sagar Shankaran, Founder of CallSphere
VAD doesn't make ASR more accurate — it controls endpointing latency, barge-in feel, and turn-taking. We tune Silero VAD threshold, prefix_padding, and silence_duration_ms with real production traces.
Key takeaways
TL;DR — VAD's job is not transcription — it's deciding when the user stopped. Tune
thresholdfor noise,silence_duration_msfor endpoint latency,prefix_padding_msfor capture safety. Default settings rarely work; build a harness that measures FAR/h and end-of-speech delay distributions per vertical.
VAD lives at the front of every voice turn. A too-eager VAD endpoints mid-word and you cut the caller off. A too-lazy VAD waits an extra 500ms after silence and you blow the latency budget. Most platforms ship a default that is wrong for your acoustic profile.
The VAD adds three controllable delays:
Typical OpenAI Realtime defaults: threshold 0.5, prefix_padding 300ms, silence_duration 500ms. That 500ms is where most of the "feels slow" complaints originate.
flowchart LR
AUDIO[Audio frames] --> NN[Silero NN]
NN --> PROB[Speech prob]
PROB --> THR{> threshold?}
THR -->|Yes| ON[Speech ON<br/>capture w/ prefix_padding]
THR -->|No| HOLD{Silence<br/>> silence_duration_ms?}
HOLD -->|Yes| END[End-of-speech]
HOLD -->|No| ON
CallSphere uses server-side VAD on OpenAI Realtime PCM16 24kHz for Healthcare, plus Silero VAD in the FastAPI :8084 path for other verticals. Each of the 6 verticals ships with a tuned VAD profile (e.g. salons run noisy, so threshold 0.55; legal intake runs quiet, so threshold 0.4). 37 agents, 90+ tools, 115+ DB tables. Pricing $149/$499/$1,499, 14-day trial, 22% affiliate.
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threshold for FAR < 5/h on the noisy vertical, then check ASR WER didn't degrade.silence_duration_ms from 500 → 250-300 for fast-feeling agents; raise it for callers who pause mid-sentence (elderly, complex intake).prefix_padding_ms if you hear clipped first words; decrease if it's bloating buffers.Q: Does better VAD mean better ASR? No. ASR has its own VAD internally. Better VAD = better feel.
Q: Should I use Silero or WebRTC's built-in VAD? Silero — neural, far more robust to noise and music.
Q: What's a good silence_duration_ms? 250-400ms for transactional voice agents, 500-700ms for support/intake.
Q: Does VAD help with barge-in? Yes — it's the trigger that detects the user starting to speak during agent TTS.
Q: How does CallSphere update VAD profiles? Weekly recalibration job re-fits thresholds against the last 10k labeled calls per vertical.
Tuning VAD for AI Voice Agents: Thresholds, Hangover, Hysteresis (2026) is also a cost-per-conversation problem hiding in plain sight. Once you instrument tokens-in, tokens-out, tool calls, ASR seconds, and TTS seconds against booked-revenue per call, the right tradeoff between Realtime API and an async ASR + LLM + TTS pipeline becomes obvious — and it's almost never the same answer for healthcare as it is for salons.
Still reading? Stop comparing — try CallSphere live.
CallSphere ships complete AI voice agents per industry — 14 tools for healthcare, 10 agents for real estate, 4 specialists for salons. See how it actually handles a call before you book a demo.
Production AI agents live or die on three loops: evals, retries, and handoff state. CallSphere runs 37 agents across 6 verticals, each with its own eval suite — synthetic call transcripts replayed nightly with assertion checks on extracted entities (date, time, party size, insurance, address). Without that loop, prompt regressions ship silently and you only find out when bookings drop.
Structured tools beat free-form text every time. Our 90+ function tools all enforce JSON schemas validated server-side; if the model hallucinates an integer where a string is required, we retry with a corrective system message before falling back to a deterministic path. For long-running flows, we treat agent handoffs as a state machine — booking → confirmation → SMS — so context survives turn boundaries.
The Realtime API vs. async decision usually comes down to "is the user holding the phone right now?" If yes, Realtime; if no (callback queue, after-hours voicemail), async wins on cost-per-conversation, which we track per agent in 115+ database tables spanning all 6 verticals.
How does this apply to a CallSphere pilot specifically? Setup runs 3–5 business days, the trial is 14 days with no credit card, and pricing tiers are $149, $499, and $1,499 — so a vertical-specific pilot is a same-week decision, not a quarterly project. For a topic like "Tuning VAD for AI Voice Agents: Thresholds, Hangover, Hysteresis (2026)", that means you're not starting from scratch — you're configuring an agent template that's already been hardened across thousands of conversations.
What does the typical first-week implementation look like? Day one is integration mapping (scheduler, CRM, messaging) and prompt tuning against your top 20 real call transcripts. Day two through five is shadow-mode running, where the agent transcribes and recommends but a human still answers, so you can compare side-by-side. Go-live is the moment your eval pass-rate clears your internal bar.
Where does this break down at scale? The honest answer: it scales until your tool catalog gets stale. The agent is only as good as the integrations it can actually call, so the operational discipline is keeping schemas, webhooks, and fallback paths green. The platform handles the rest — observability, retries, multi-region routing — without your team owning the GPU layer.
Want to see how this maps to your stack? Book a live walkthrough at calendly.com/sagar-callsphere/new-meeting, or try the vertical-specific demo at escalation.callsphere.tech. 14-day trial, no credit card, pilot live in 3–5 business days.
Written by
Sagar Shankaran· Founder, CallSphere
Sagar Shankaran is the founder of CallSphere, where he builds production AI voice and chat agents deployed across healthcare, hospitality, real estate, and home services. He writes about agentic AI, LLM engineering, and shipping voice agents that handle real calls in production.
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