Reducing Voice Agent Latency with Forced End-of-Utterance

If you’re building a real-time voice agent, you’ve probably seen this problem: the user finishes speaking… and then nothing happens. That gap — even just a couple of seconds — breaks conversational flow and makes voice agents feel slow or unnatural. In this video, we explain why end-of-utterance detection causes awkward pauses, and how forcing end-of-utterance can dramatically improve responsiveness in real-time Voice AI systems. You’ll learn: - Why default end-of-speech detection often fails in real conversations - How latency and silence thresholds impact turn-taking - When and why to force end-of-utterance in production voice agents - How high-accuracy, low-latency speech recognition enables more natural dialogue This is a critical building block for AI voice agents, conversational AI, and real-time speech applications. Built with Speechmatics, delivering: - Low-latency real-time transcription - Robust accuracy in messy, real-world audio - Reliable turn-taking for voice agents at scale 🔗 Learn more about Voice AI and agent use cases: https://www.speechmatics.com/use-cases/ai-voice-agents 🔗 Explore Speechmatics real-time speech recognition: https://www.speechmatics.com/speech-to-text 🔗 Get started in the developer portal: https://portal.speechmatics.com 🔗 Hands-on tutorials in the Speechmatics Academy https://github.com/speechmatics/speechmatics-academy Follow Speechmatics: 🔗 LinkedIn: https://www.linkedin.com/company/speechmatics 🔗 X (Twitter): https://x.com/speechmatics