The maintainer of speech-core, a C++17 voice-pipeline runtime used by Swift and Android speech libraries, released v0.0.14 with an optional end-of-turn gate using Pipecat/Daily's Smart Turn v3.2 model. It prevents brief pauses from prematurely finalizing transcription and invoking the LLM before users finish speaking.
Developers seek ultra-low-latency alternatives to Silero VAD for speculative voice-agent pipelines
Developers seek ultra-low-latency alternatives to Silero VAD for speculative voice-agent pipelines
An open-source voice agent that runs entirely on an Android phone using a 270M parameter LLM (FunctionGemma) with LoRA adapters for tool calling. It performs VAD, streaming STT, tool-calling, device actions, and TTS in 1.2 GB RAM, responding 0.9s after user stops speaking. Solves on-device agent reliability for mobile users without cloud dependency.
An open-source voice agent that runs entirely on an Android phone using a 270M parameter LLM (FunctionGemma) with LoRA adapters for tool calling. It performs VAD, streaming STT, tool-calling, device actions, and TTS in 1.2 GB RAM, responding 0.9s after user stops speaking. Solves on-device agent reliability for mobile users without cloud dependency.
An open-source framework that gives LLM agents continuous audio awareness beyond speech-to-text, detecting environmental sounds like birds, breaking glass, or smoke alarms. It runs locally with CLAP, Whisper, Silero VAD, and sqlite-vec, and uses fast-agent to support any LLM provider including local Ollama models.
An open-source framework that gives LLM agents continuous audio awareness beyond speech-to-text, detecting environmental sounds like birds, breaking glass, or smoke alarms. It runs locally with CLAP, Whisper, Silero VAD, and sqlite-vec, and uses fast-agent to support any LLM provider including local Ollama models.
A voice AI tutor that uses a small, fast model instead of a frontier model to achieve low latency. The scaffolding around the model provides intelligence, while the model choice prioritizes speed to first token. It solves the problem of voice agents feeling broken due to pauses, targeting developers building real-time voice applications.
A voice AI tutor that uses a small, fast model instead of a frontier model to achieve low latency. The scaffolding around the model provides intelligence, while the model choice prioritizes speed to first token. It solves the problem of voice agents feeling broken due to pauses, targeting developers building real-time voice applications.
Friendo is a call-native voice agent that can initiate phone calls or take live calls via LiveKit WebRTC. It uses a cascaded stack of Deepgram, Claude, and ElevenLabs to achieve low-latency voice interactions with full control over tool calls and memory. It solves the problem of robotic, laggy voice AI by optimizing latency and state management.
Friendo is a call-native voice agent that can initiate phone calls or take live calls via LiveKit WebRTC. It uses a cascaded stack of Deepgram, Claude, and ElevenLabs to achieve low-latency voice interactions with full control over tool calls and memory. It solves the problem of robotic, laggy voice AI by optimizing latency and state management.