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
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.
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.
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.
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.
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.
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.
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.
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
| 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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