#voice
6 articles
Voice AI latency budget: hitting sub-500ms in production
A systematic breakdown of every millisecond in the voice AI pipeline and the specific techniques that compound to sub-500ms time-to-first-audio in production.
Voice Agent Frameworks: Vapi vs LiveKit vs Pipecat
Compare Vapi, LiveKit Agents, and Pipecat across latency, cost, telephony, and control — with the exact break-even math to pick the right abstraction.
VAD and Turn Detection: The Hardest UX Problem in Voice AI
How voice activity detection and turn-taking work in real-time AI agents — energy vs semantic VAD, barge-in handling, and why getting this wrong is the top user complaint.
Cascaded pipeline vs native speech-to-speech: when to use each
Chain STT, LLM, and TTS for control — or use one speech-native model for latency. The real tradeoffs, with numbers, and when each architecture wins.
The Voice Pipeline: STT to LLM to TTS End-to-End
Build the STT to LLM to TTS voice pipeline end-to-end — streaming each stage, budgeting latency, and hitting sub-second time-to-first-audio.
Modalities Explained: From Text-Only to Omni Models
What modalities are, how frontier models encode images, audio, and video into transformer attention, and how to pick the right model for your pipeline in 2026.