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TEN FRAMEWORK
Build real-time voice AI agents with multi-modal capabilities
ABOUT
Building real-time voice AI agents is significantly harder than text-based agents — it requires managing audio pipelines, speech-to-text, text-to-speech, voice activity detection, and low-latency streaming, all orchestrated across multiple models. TEN Framework provides a complete infrastructure for these pipelines: connect a wake-word detector, an ASR model, an LLM, and a TTS engine into a working voice agent with minimal glue code. It handles the real-time streaming, buffering, and synchronization that makes conversational voice agents feel natural.
INTEGRATION GUIDE
1. Build a voice-based customer support agent that can hear, understand, and speak back in real time
2. Create a real-time transcription and analysis pipeline for meetings with multi-modal context
3. Build a voice assistant for physical spaces that responds to wake words with low latency
4. Deploy a multi-modal agent that processes both speech input and camera feed simultaneously
5. Prototype conversational AI experiences with customizable voice pipelines from multiple providers
TAGS
agentsvoicereal-timemulti-modalframeworkai