Streaming processes data incrementally as it arrives rather than waiting for complete input. For voice AI, streaming enables real-time speech recognition and progressive response delivery that maintains natural conversation flow.
How does streaming work in voice AI?
Audio streams to the speech recognition system, which produces transcription results progressively. The language model may begin processing before the caller finishes speaking. Response generation streams to text-to-speech, which begins producing audio immediately. Each component processes data as it becomes available.
Why does streaming matter?
Without streaming, the system would wait for complete utterances before processing, then wait for complete responses before speaking. This adds seconds of latency that destroys conversational flow. Streaming enables the sub-second response times that make voice AI feel natural.
Streaming in practice
A caller begins speaking a long sentence. Within 100ms, streaming ASR starts producing partial transcripts. The AI begins considering likely intents before the caller finishes. When the utterance ends, response generation starts immediately with most context already processed. Audio streams to the caller as it is generated. Total latency is 350ms despite processing complexity.