{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Machine Learning Tech Brief By HackerNoon","title":"The Voice Agent Latency Playbook: STT, Turn Detection, and the Tradeoffs Nobody Talks About","html":"","width":"100%","height":180,"duration":878,"description":"\n This story was originally published on HackerNoon at: https://hackernoon.com/the-voice-agent-latency-playbook-stt-turn-detection-and-the-tradeoffs-nobody-talks-about.\nFind the hidden causes of slow voice agents and learn how to achieve roughly one-second responses without sacrificing accuracy.\nCheck more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.\n You can also check exclusive content about #ai, #voice-ai, #voice-agent-latency, #reduce-voice-latency, #faster-voice-agents, #text-to-speech-latency, #real-time-voice-agents, #voice-ai-performance, and more.\nThis story was written by: @assemblyai. Learn more about this writer by checking @assemblyai's about page,\n and for more stories, please visit hackernoon.com.\nUsers don't feel your STT or TTS latency—they feel how long until the agent responds correctly. The biggest wins aren't a faster model: they're fixing end-of-turn detection (stop using fixed silence timeouts), streaming all three stages so they overlap, and cutting provider hops. The trap most teams fall into is trading accuracy for speed at the STT layer—but a mis-heard name or number forces a correction loop that costs a full extra turn, wiping out whatever you saved. Optimize turns-to-resolution, not transcript speed, and measure per-stage with P50/P90/P95.\n \n ","thumbnail_url":"https://img.transistorcdn.com/KyA01h2FD2insgk-wX_xzV6vbJnTNl2BvPYVL-XaI9A/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzQxMjcyLzE2ODM1/ODI0ODgtYXJ0d29y/ay5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}