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Voice OS · 2026

Endpointing in Voice AI

Endpointing is the decision a voice AI makes about when the user has finished speaking. Get it wrong in one direction and the AI cuts the user off mid-thought. Get it wrong in the other and there is an awkward 2 second pause after every sentence. Endpointing is one of the hardest design problems in voice AI because the right answer depends on the user's speech pattern, the topic, the noise environment, and how much they want to think out loud. It is rarely solved with a single threshold.

WHAT TO LOOK FOR

The three things that actually matter

1

Silence threshold

The simplest endpointing signal: how long of a gap before deciding the user is done. Transactional voice AI uses 200 to 400 milliseconds; conversational voice AI uses 500 to 900 milliseconds; thoughtful long-form voice AI can use over a second. The right value depends on what the user is doing.

2

Syntactic completion

A fragmentary sentence like 'I want to' is unlikely to be a finished thought even after 800 milliseconds of silence. A complete sentence ending in a verb-object structure is much more likely. Modern endpointing uses lightweight syntax checks to extend or shrink the silence threshold.

3

Prosodic cues

Falling intonation at the end of an utterance signals completion; rising intonation signals a question or continuation. Using prosody as an endpointing signal is technically harder but produces more natural turn-taking, especially for users who think out loud.

TLDR:Lucy OS1 uses adaptive endpointing tuned for thinking-out-loud conversations. The default silence threshold is 700 milliseconds, longer than the 400 milliseconds typical of transactional voice AI, because Lucy users tend to pause mid-thought. The threshold extends further when the user is mid-sentence by syntactic cues, and shortens when the user has clearly finished. The effect is a voice AI that does not interrupt when you are gathering your thoughts, but also does not feel slow when you have finished a clear request.

Why Lucy OS1

Silence threshold

The simplest endpointing signal: how long of a gap before deciding the user is done. Transactional voice AI uses 200 to 400 milliseconds; conversational voice AI uses 500 to 900 milliseconds; thoughtful long-form voice AI can use over a second. The right value depends on what the user is doing.

Syntactic completion

A fragmentary sentence like 'I want to' is unlikely to be a finished thought even after 800 milliseconds of silence. A complete sentence ending in a verb-object structure is much more likely. Modern endpointing uses lightweight syntax checks to extend or shrink the silence threshold.

Prosodic cues

Falling intonation at the end of an utterance signals completion; rising intonation signals a question or continuation. Using prosody as an endpointing signal is technically harder but produces more natural turn-taking, especially for users who think out loud.

Filler word detection

Words like 'um', 'uh', 'you know', and 'so' often precede continuation. Detecting them lets the endpointer hold the turn open even after a long pause, which prevents the AI from cutting off a user mid-thought.

Mid-sentence pause grace

When the user is clearly mid-sentence, endpointing extends the silence threshold dynamically. A 500 millisecond pause after 'I think the answer is' should not trigger response, even though the same pause after 'thanks' should.

Push-to-talk override

For environments where automatic endpointing is unreliable, like noisy cars or speakerphones, a push-to-talk button gives the user explicit control. Lucy OS1 supports this as a fallback for environments where automatic endpointing struggles.

QUICK COMPARISON

Lucy OS1 vs most AI tools

Capability Lucy OS1 Most AI tools
Memory across sessions ✓ Permanent, never resets ✗ Resets after every session
Voice quality ✓ Lucy OS1 Natural Voice (best-in-class) ✗ Basic STT, struggles with noise
Calendar awareness ✓ Reads Google Calendar in real time ✗ No calendar access
Available 24/7 Always on, any device Available but stateless each time
Gets personal over time ✓ Builds your context continuously ✗ Starts from zero every session

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1

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2

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3

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Frequently Asked Questions

Why does Siri sometimes cut me off mid-sentence?
Most consumer voice assistants use silence thresholds around 400 milliseconds, optimized for short transactional commands like 'set a timer'. That threshold is too short for thinking-out-loud conversations, which is why they feel like they interrupt.
What is the right silence threshold for conversational AI?
For natural conversation, 600 to 800 milliseconds works well for most speakers. For thoughtful or analytical conversation, 1 second or longer is appropriate. The threshold should be tunable per user and per context.
Can endpointing be done client-side or does it need a server?
Voice activity detection runs client-side. Endpointing decisions can run client-side too, but server-side endpointing has access to more context, including the running transcript, which improves accuracy. Most production systems do both.
What happens when the user pauses and the AI responds before they finish?
The user starts speaking again and the AI must barge-in handle: stop generating, stop TTS, and process the new utterance as a continuation or correction. Good barge-in handling makes endpointing errors recoverable rather than annoying.
Does endpointing improve with longer conversations?
Yes, when the system tracks per-user speech patterns. A user who typically pauses for 800 milliseconds mid-thought will have their threshold adjusted upward over the first few sessions, which produces better turn-taking over time.
How does background music or TV affect endpointing?
Background audio above the noise floor can fool simple silence detectors. VAD models trained on noisy data handle most cases, but very loud or speech-like background audio degrades endpointing accuracy. Headsets eliminate the problem.

MORE IN THIS CATEGORY

→ Voice OS Architecture → The Voice AI Audio Pipeline → Voice AI Latency Budget → Barge-In and Interruption Handling → Wakeword Detection → The Memory Layer of a Voice OS → Voice OS Context Window → Voice OS Permissions Model → See all

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Lucy OS1 vs Siri → Lucy OS1 vs ChatGPT → Lucy OS1 vs Google Gemini → Lucy OS1 vs Google Assistant → Lucy OS1 vs Amazon Alexa → See all comparisons →

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