Open-source, native audio turn detection model
Our goal with this project is to build a completely open source, state of the art turn detection model that can be used in any voice AI application. I've been experimenting with LLM voice conversations since GPT-4 was first released. (There's a previous front page Show HN about Pipecat, the open source voice AI orchestration framework I work on. [1]) It's been almost two years, and for most of that time, I've been expecting that someone would "solve" turn detection. We all built initial, pretty good 80/20 versions of turn detection on top of VAD (voice activity detection) models. And…
Open-source, native audio turn detection model launched on March 6, 2025 with 126 votes, #359 of 7,215 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 1 year on.
In plain words
This project is an open-source turn detection model designed for voice AI applications. It determines when a speaker has finished talking in conversation, which is essential for natural dialogue in voice assistants. The model addresses a gap in the voice AI ecosystem where developers previously relied on voice activity detection or slower context-aware alternatives. Built to be state-of-the-art and readily usable across different voice AI systems, it aims to improve the responsiveness and naturalness of automated voice conversations.
written from the facts on this page · September 2026
From the sources
Contribute to pipecat-ai/smart-turn development by creating an account on GitHub.
An open source, community-driven, native audio turn detection model. Turn detection is one of the most important functions of a conversational voice AI technology stack. Turn detection means deciding when a voice agent should respond to human speech. Most voice agents today use voice activity detection (VAD) as the basis for turn detection. VAD segments audio into "speech" and "non-speech" segments. VAD can't take into account the actual linguistic or acoustic content of the speech. Humans do turn detection based on grammar, tone and pace of speech, and various other complex audio and semantic cues. We want to build a model that matches human expectations more closely than the VAD-based…from github.com
In the maker’s words, at launch
Our goal with this project is to build a completely open source, state of the art turn detection model that can be used in any voice AI application. I've been experimenting with LLM voice conversations since GPT-4 was first released. (There's a previous front page Show HN about Pipecat, the open source voice AI…
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