CalmCue reduces sensory overload in voice chat by adapting audio dynamics in real time:
leveling loudness, reducing overlap, and offering gentle turn-taking cues.
No toxicity detection. No content classification. Only overlap, interruptions, and loudness spikes.
Detects sustained overlap and helps you hear the dominant speaker.
Smooth leveling reduces sudden loudness spikes and jumps.
Opt-in summaries help you rejoin after overload moments.
In many voice chats, the hard part isn’t what people are saying—it’s the audio dynamics: overlap, interruptions, and sudden loudness changes. For a lot of people (especially neurodivergent folks), that turns into fatigue, anxiety, or “I can’t follow this anymore.”
When multiple people talk at once, the brain does extra work just to parse who’s speaking and what to track.
CalmCue is not a toxicity detector. It doesn’t interpret meaning. It just smooths the room so you can stay present.
Keep the conversation intact, but make it easier on the nervous system.
Reduce cognitive load from chaotic voice chat—without changing what anyone is allowed to say.
Tracks overlap ratio, interruptions, and loudness spikes in real time. Converts signals into an explainable 0–100 score.
When overlap persists, CalmCue offers a gentle toast: “Let Speaker A finish before Speaker B.”
Smoothly levels loudness and ducks the non-dominant speaker during sustained overlap to improve intelligibility.
If chaos stays high, CalmCue can send you a private recap of the last 15–120 seconds—so you can rejoin without stress.
A lightweight pipeline that stays away from content and focuses on dynamics.
RMS → dB, voice activity, rolling baseline, overlap windows.
Weighted sum of overlap, interruptions, spikes → 0–100 score.
Leveling, ducking, nudges, and optional recap prompts.
chaosScore = 55% overlap + 25% interruptions + 20% loudness spikes (scaled & capped). No “meaning” is inferred from speech.
Clear boundaries, simple answers.
No. CalmCue does not analyze content, intent, sentiment, or policy. It only measures overlap/interruptions/loudness dynamics.
This site positions CalmCue as dynamics-first. Your product can process audio locally when possible and store only aggregated telemetry.
No. The recap is private to the user who requests it (DM-style), not posted to the room.
Anyone who gets overwhelmed by chaotic voice rooms—especially neurodivergent folks, anxious listeners, and accessibility-first teams.
CalmCue can adapt its dynamics settings based on lightweight feedback—without analyzing what was said. Updates are rate-limited, clamped, and applied only at session end.
We aggregate feedback during the session, then apply a single policy update only when the session ends
(/api/session/end).
Parameter changes are clamped to safe ranges, with a maximum of 10% change per session to prevent oscillation or “surprise” behavior.
What feedback can adjust (examples):
Each update creates a new Policy vN in Postgres, and caches the latest policy in localStorage so the next run starts from your last known-good settings.
Transcripts are not used for policing. Any text is used only for recap summarization when the user opts in.
CalmCue stays dynamics-first. These integrations add captions, private recaps, and real observability—without turning into content policing.
Modulate’s Velma Transcribe gives CalmCue live captions and a rolling transcript with speaker labels and timestamps. We use that transcript only to generate the user’s private recap when they opt in—never for moderation, filtering, or policing.
When chaos stays high for a bit, CalmCue can offer a private recap to help you rejoin. We send only the last 15/30/60/120 seconds (your choice) for summarization, and fall back to a lightweight heuristic if needed.
We log focus summaries and session-end events as traces so you can debug any “why did it do that?” moment and build an eval dataset over time.
We track how CalmCue behaves over time: reward trends, overlap seconds per policy version, and “first vs second run” improvements after policy learning.
Integrations are opt-in. CalmCue’s core behavior never depends on content understanding—only dynamics signals.
CalmCue’s core idea works anywhere people talk over each other—so the natural next step is making it easy to plug into the tools teams already live in.
Shared defaults with personal comfort profiles—so individuals can opt into what helps them without forcing it on everyone.
Bring dynamics smoothing, gentle turn-taking cues, and private recaps into existing voice/video calls.
More control over what “calm” means for you—without turning it into moderation.
Use Braintrust logs + user feedback to test changes safely and prove “this actually reduced overload.”
CalmCue becomes a “comfort layer” for voice/video—integrated into the places people already meet, without changing the conversation itself.