Glossary
What is latency in voice AI?
Definition
Latency in voice AI is the delay between when a caller finishes speaking and when the system responds. It is measured in milliseconds and accumulates across each processing step. Low latency is essential for conversations that feel natural rather than awkward.
01Where latency comes from
In a voice assistant, latency builds up across several stages: transmitting audio, recognizing speech, understanding and generating a response, synthesizing speech, and sending it back. Each stage adds time, and network conditions can add more. The total round-trip delay is what the caller actually perceives.
02Why latency matters on calls
Human conversation relies on quick turn-taking, so long pauses feel unnatural and can make callers repeat themselves or talk over the system. Keeping end-to-end latency low helps the assistant respond at a conversational pace. Techniques like streaming recognition and generating speech incrementally reduce perceived delay.
03Measuring and reducing latency
Latency is typically reported in milliseconds and can be broken down per stage to find bottlenecks. Approaches to reduce it include streaming instead of waiting for complete input, using faster models, and processing steps in parallel. There is often a trade-off between speed, cost, and response quality.
Frequently asked questions
How is voice AI latency measured?
It is measured in milliseconds, usually from the moment the caller stops speaking to when the system begins its spoken reply, and can be broken down by processing stage.
Why does low latency matter?
Natural conversation depends on quick turn-taking, so lower latency prevents awkward pauses and reduces the chance that callers repeat themselves or talk over the system.
See also
Related terms
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