TwinsAI
Glossary

Voice-to-voice latency

Voice-to-voice latency is the time between when a person finishes speaking and when an AI voice agent begins to respond. It is the key measure of how natural a spoken AI conversation feels, since long delays read as robotic or like a dropped call.

Voice-to-voice latency sums every step in the loop: capturing audio, speech-to-text, the language model deciding what to say, text-to-speech, and network transit. Human conversation has gaps of only a couple hundred milliseconds, so when an AI voice agent exceeds roughly 700ms the pause becomes noticeable and prospects start to hang up. This is also why a parallel dialer that bridges a human creates a connect pause. TwinsAI's AI dialer engineers around the problem with sub-400ms voice-to-voice on every call leg, as detailed in the Nooks comparison.

Frequently asked

What is a good voice-to-voice latency for an AI phone agent?

Under about 700ms the conversation starts to feel natural, and the lower the better; TwinsAI targets sub-400ms voice-to-voice. Above that threshold the delay reads as awkward dead air and prospects are more likely to hang up.

Why does voice-to-voice latency matter on sales calls?

On a cold call the prospect is already primed to disconnect, so any noticeable delay after they speak signals an automated system and increases hang-ups. Low latency is what makes an AI voice agent sound like a real person rather than a robocall.

Related terms
AI voice agentAI dialerParallel dialerWarm transfer

TwinsAI is an AI voice agent that runs outbound sales calls end to end: it dials, qualifies, and books meetings, then warm-transfers a human when it matters.

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