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Comment by koljab

I built RealtimeVoiceChat because I was frustrated with the latency in most voice AI interactions. This is an open-source (MIT license) system designed for real-time, local voice conversations with LLMs.

Quick Demo Video (50s): https://www.youtube.com/watch?v=HM_IQuuuPX8

The goal is to get closer to natural conversation speed. It uses audio chunk streaming over WebSockets, RealtimeSTT (based on Whisper), and RealtimeTTS (supporting engines like Coqui XTTSv2/Kokoro) to achieve around 500ms response latency, even when running larger local models like a 24B Mistral fine-tune via Ollama.

Key aspects: Designed for local LLMs (Ollama primarily, OpenAI connector included). Interruptible conversation. Smart turn detection to avoid cutting the user off mid-thought. Dockerized setup available for easier dependency management.

It requires a decent CUDA-enabled GPU for good performance due to the STT/TTS models.

Would love to hear your feedback on the approach, performance, potential optimizations, or any features you think are essential for a good local voice AI experience.

The code is here: https://github.com/KoljaB/RealtimeVoiceChat

parent koljab 1 year ago

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