Superleap Voice Platform

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One-click presets

How the agent decides when to speak & whether you can interrupt

Two independent pipelines control conversation flow. Tuning one doesn't affect the other.

Pipeline A — Response speed

After the user stops speaking, the agent waits, watches a turn-detector ML model, then commits to reply.


wait = MIN(
  Take turn,
  Response rate floor + Linear delay
) + turn-detector hesitation

where Response rate floor =
  Rapid → 200ms · Balanced → 500ms · Patient → 1000ms
  Custom → whatever you type in Endpointing

There's also a ~250ms VAD silence floor underneath everything (Silero default, hardcoded). It stacks BEFORE this formula starts counting.

Pipeline B — User interrupting the agent

While the agent is speaking, the user's voice may cut it off. Cutoff requires ALL of:


  AEC warmup has elapsed
  user speech ≥ Min interrupt
  user words ≥ Min words

Settings reference

Setting	What it does	Default	Snappy	Phone	Patient
Response speed (Pipeline A)
Response rate	Minimum silence wait after you stop speaking before the agent replies. Rapid=200ms, Balanced=500ms, Patient=1000ms, Custom=reveals an Endpointing input where you type the exact ms.	Balanced	Rapid	Balanced	Patient
Endpointing (ms)	Only visible when Response rate = Custom. Sets the exact silence floor in milliseconds.	—	—	—	—
Linear delay (ms)	Padding added ON TOP of the floor. Lets you give extra breathing room for thinkers without changing the preset.	0	0	0	200
Take turn (ms)	Ceiling. If turn-detector ML stays uncertain this long, force-commit the turn anyway.	2000	1000	1500	3000
Turn-detector threshold	Confidence (0–1) the semantic EOU model needs before committing a turn within `min_delay`. Below threshold the session keeps waiting up to Take turn. Empty = use the model's per-language default.	auto	auto	auto	0.35
User interruption — how callers cut into the agent (Pipeline B)
AEC warmup (sec)	After call starts, NO interrupts allowed for this long while echo-cancellation converges. Lower = snappier early interrupts, higher = cleaner audio.	0.5	0.3	1.0	1.5
Min interrupt (ms)	Your speech must last at least this long to count as an interruption. Lower = easier interrupt, more false positives.	300	200	400	600
Min words	Your transcript must contain at least this many words. `1` = even "stop" interrupts.	2	1	2	3
Resume false intrr.	If you triggered an interrupt but stopped quickly, resume the agent's cut-off reply automatically.	ON	ON	ON	ON
Resume after (sec)	How long to wait before resuming the cut-off reply.	1.5	1.5	1.5	2.0
Other
Preemptive LLM	Start the LLM call before turn-detector fully commits. Saves ~250 ms per turn.	ON	ON	ON	ON
IVR detection	Detect "Press 1 for sales" auto-attendants. Mainly useful for outbound calls to call centres.	OFF	OFF	OFF	OFF
Welcome delay (ms)	Sleep this long before the agent's first greeting. Useful when phone audio path needs a moment to settle.	0	0	500	0
Hangup on silence	Auto-disconnect if the user is silent for the threshold. Useful for unmanned outbound.	OFF	OFF	OFF / 30s	OFF
Online check msg / after	Probe the user with a short message after N seconds of silence ("Are you still there?"). Fires before hangup.	"Are you still there?" / 9s	—	"Are you still there?" / 10s	"Still there?" / 20s
Max duration (sec)	Hard ceiling on call length. Defensive against runaway calls.	600	600	900	900
STT — Deepgram Nova advanced
DG endpointing (ms)	Silence Deepgram waits before emitting its own end-of-utterance hint. The plugin's built-in 25ms is far too aggressive — Deepgram themselves recommend 300–500ms. Lower = snappier but more mid-sentence cutoffs on slow speakers.	300	200	300	500
DG filler words	Keep "um"/"uh"/"hmm" in the transcript. When OFF those tokens get stripped and the turn-detector sees a "done" transcript while the user is still hesitating — the #1 cause of premature EOU.	ON	ON	ON	ON
DG smart format	Add punctuation, numeric formatting, etc. to transcripts. Improves prompt readability and unlocks future punctuation-based endpointing modes.	ON	ON	ON	ON
STT — Deepgram Flux advanced (server-side EOU)
EOT threshold	Confidence (0.5–0.9) Flux's own end-of-turn model needs before declaring EOT. Plugin default 0.7. Lower = snappier but more mid-sentence cutoffs.	0.7	0.5	0.7	0.8
EOT timeout (ms)	Maximum ms Flux waits for a confident EOT before forcing one. Plugin default 3000. Lowering trims worst-case latency at the cost of cutting off slow speakers.	3000	2000	3000	4500
Eager EOT	Early-fire confidence (0.3–0.9) that lets Flux emit a "likely end of turn" signal ahead of the final EOT, so preemptive LLM generation can kick in sooner. Must be ≤ EOT threshold. Blank = disabled.	off	0.3	off	off

Scenarios — what to tune for what

"Faster response, please"

Set Response rate → Rapid (drops floor 500→200ms)
Set Linear delay → 0 (removes additive padding)
Set Take turn → 1000ms (force commit sooner when uncertain)
Keep Preemptive LLM ON (saves another ~250ms)
Lower STT model latency — Deepgram Flux beats Sarvam Saaras by ~200ms

Expected EOU drop: 1.5s → 0.6s

"Easier to interrupt the agent"

Lower AEC warmup → 0.3s (interrupts work right from call start)
Lower Min interrupt → 200ms (shorter user speech triggers)
Lower Min words → 1 (even "stop" works)
Keep Resume false intrr. ON (recovers from accidental cuts)

Risk: more false positives. Coughs, breaths, background TV → may cut off the agent. Bump back up if it happens.

"Stop the agent from cutting off slow users"

Set Response rate → Patient (1s floor)
Set Take turn → 3000ms (allow long pauses)
Add Linear delay → 300ms (extra padding)
Raise Min words → 3 (don't react to single "um" interjections)

Trade-off: slower replies. Use only if users are elderly / non-native / pause a lot.

"Phone calls dropping noisy interrupts"

Set AEC warmup → 1.0s (phone AEC needs more convergence)
Set Min interrupt → 400ms (filter line noise)
Set Min words → 2 (filter cough/breath)
Try a different noise-cancellation on the SIP trunk

"Outbound calls hitting IVR menus"

Turn IVR detection ON
Raise Min words → 3 (avoid reacting to "Press 1 for…")
Bump Max duration → 900s (IVR navigation can take time)

"Latency feels high — where's the time going?"

Watch the live Latency Breakdown card during a call. Numbers come from real metrics.

STT > 500ms → switch from Sarvam Saaras to Deepgram Nova-3 (multilingual) or Flux (English).
EOU > 1s → tune Pipeline A above. Common cause: Response rate set to Balanced/Patient with no Endpointing override.
LLM > 1.5s TTFT → switch from gpt-4o to gpt-4o-mini, or Llama-3.3-70B on Groq (sub-200ms TTFT).
TTS > 400ms TTFB → use Sarvam Bulbul (real-time) instead of OpenAI TTS (batch).

"Agent cuts me off when I say 'umm'"

The STT is committing end-of-turn during the brief pause before the filler word lands.

Open STT → Deepgram (advanced) in the Models column.
If using Nova — turn Filler words ON and bump DG endpointing → 400ms (default 25ms is way too aggressive).
If using Flux — raise EOT threshold → 0.8 and EOT timeout → 4000ms so Flux waits longer before declaring end-of-turn. Leave Eager EOT blank.
Raise Turn-detector threshold → 0.25–0.35 so the semantic model is more cautious during borderline pauses.
Optionally raise Linear delay → 200ms for extra breathing room.

Works best with Hindi / multilingual callers who naturally use "matlab" / "yaani" / "haan" as fillers.

How saving works

Every knob on this page round-trips through configs/default.json:

Tweak any knob in the UI.
Click Save as default in the header.
The config is persisted; the next call (web or phone) loads it.
Refresh the page → the UI reads back from default.json, so what you saved is what you see.

Phone calls (Plivo / Twilio) don't carry per-call overrides, so they always use the saved default. For web calls, the UI can also send overrides per-call without saving.

Speech to text

Language model

Text to speech

Persona & voice

Turn & language

Per-minute cost

Conversation behavior

Response

Welcome

Call management

Greeting (opening line)

Prompt prefix (auto)

Base prompt

Latency breakdown

Live calls

Active calls